U.S. patent application number 13/935663 was filed with the patent office on 2013-12-19 for high energy, real time capable, direct radiation conversion x-ray imaging system for cd-te and cd-zn-te based cameras.
The applicant listed for this patent is OY AJAT LTD.. Invention is credited to Tuomas PANTSAR, Konstantinos SPARTIOTIS.
Application Number | 20130334433 13/935663 |
Document ID | / |
Family ID | 34978705 |
Filed Date | 2013-12-19 |
United States Patent
Application |
20130334433 |
Kind Code |
A1 |
SPARTIOTIS; Konstantinos ;
et al. |
December 19, 2013 |
HIGH ENERGY, REAL TIME CAPABLE, DIRECT RADIATION CONVERSION X-RAY
IMAGING SYSTEM FOR CD-TE AND CD-ZN-TE BASED CAMERAS
Abstract
A calibrated real-time, high energy X-ray imaging system is
disclosed which incorporates a direct radiation conversion, X-ray
imaging camera and a high speed image processing module. The high
energy imaging camera utilizes a Cd--Te or a Cd--Zn--Te direct
conversion detector substrate. The image processor includes a
software driven calibration module that uses an algorithm to
analyze time dependent raw digital pixel data to provide a time
related series of correction factors for each pixel in an image
frame. Additionally, the image processor includes a high speed
image frame processing module capable of generating image frames at
frame readout rates of greater than ten frames per second to over
100 frames per second. The image processor can provide normalized
image frames in real-time or can accumulate static frame data for
substantially very long periods of time without the typical
concomitant degradation of the signal-to-noise ratio.
Inventors: |
SPARTIOTIS; Konstantinos;
(Espoo, FI) ; PANTSAR; Tuomas; (Espoo,
FI) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
OY AJAT LTD. |
Espoo |
|
FI |
|
|
Family ID: |
34978705 |
Appl. No.: |
13/935663 |
Filed: |
July 5, 2013 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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11226877 |
Sep 14, 2005 |
8530850 |
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13935663 |
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11017629 |
Dec 20, 2004 |
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11226877 |
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60585742 |
Jul 6, 2004 |
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Current U.S.
Class: |
250/370.09 |
Current CPC
Class: |
G01T 1/24 20130101; H04N
5/3655 20130101; H04N 5/367 20130101; H01L 31/0296 20130101; H04N
5/3651 20130101; H04N 5/325 20130101; H01L 27/14634 20130101 |
Class at
Publication: |
250/370.09 |
International
Class: |
G01T 1/24 20060101
G01T001/24 |
Foreign Application Data
Date |
Code |
Application Number |
Jul 1, 2005 |
IB |
PCT/IB05/01896 |
Claims
1. An x-ray imaging system, comprising: an x-ray imaging device
with an output providing an array of pixels values for producing
multiple different individual image frames (44), each said pixel
value generated responsive to absorption of impinging high energy
x-ray gamma ray radiation, converted by an analog to digital
converter (96) (ADC) providing, at the output of the imaging
device, the array of pixel values, each pixel value with a first
bit depth (N), each individual frame of said multiple individual
frames comprising the array (45) of the pixel values with the first
bit depth (N); and an image processor connected to receive the
array of pixel values from the output of the imaging device, the
image processor including a processor (24) calculating final image
pixel values (47) of a second bit depth (M) from the pixel values
of the first bit depth (N) of the different individual frames, the
image processor outputting frames of the final image pixel values
(47) of an x-ray image to be displayed on a display, wherein the
second bit depth (M) of the final image pixel values (47) to be
displayed is greater than the first bit depth of the pixel values
from the individual frames (M>N) to provide relatively increased
resolution of the image data displayed the x-ray image displayed on
the display relative to the resolution output from the x-ray
imaging device.
2. The system of claim 1, wherein, the imaging device is a high
energy x-ray imaging camera (37), the camera providing an array of
pixels values at said output of the analog to digital converter,
the camera having a high pixel density, direct conversion radiation
detector substrate (30), with pixels (36) of the detector substrate
in electrical connection to a corresponding pixel circuit (31) on
an ASIC readout substrate (32), the detector substrate providing
for directly converting the impinging high energy x-ray gamma ray
radiation (80) to an electrical charge and communicating the
electrical charge via an electrical connection (35) between the
pixel (36) to a corresponding pixel circuit on the ASIC readout
substrate (32) as an electric charge signal, and the pixel circuit,
via the analog to digital converter, providing for processing the
electric charge signal from each pixel into the pixel values with
the first bit depth (N).
3. The system of claim 1, wherein, the array of pixel values, where
each pixel value has the first bit depth (N), at the output of the
imaging device is un-corrected image pixel values, and the
processor calculates the final image pixel values (47) of the
second bit depth (M) using a normalization module (24) that
accumulates plural different frames of the first bit depth (N) to
calculate each final image pixel value (47) of the second bit depth
(M) to provide normalized, corrected image data determined from
accumulated different frames of the first bit depth (N).
4. The system of claim 2, further comprising a high speed image
frame processing module (18) in electronic communication with the
ASIC readout substrate (32) of the imaging camera (37), the frame
processing module receiving digitized pixel signals derived from a
pixel circuit output from each pixel circuit (31) of the readout
substrate and using the pixel signals to generate an image frame
(44) at a frame readout rate of greater than ten image frames per
second.
5. The system of claim 4, further comprising a calibration module
selectably in digital communication with the frame processor module
(18), the calibration module when selected being driven by a
software process including a calibration routine (20) which
calibration routine writes pixel correction data specific to each
pixel (36) in an image frame (44) to a lookup table (22).
6. The system of claim 5, wherein the lookup table is writeable by
the calibration module (20) with pixel specific correction data,
and readable by a normalization module (24).
7. The system of claim 6, wherein the normalization module (24) is
selectably in communication with the frame processor module (18)
and with the lookup table (22), the normalization module receiving
real time image frame data/record from the frame processor module
and pixel specific correction data from the lookup table, and
providing normalized image data comprising said final pixel values
(47) via a display image output for use in a display module (16) to
present said X-ray image.
8. The system of claim 7, wherein the processor calculates the
final image pixel values (47) of the second bit depth (M) using a
normalization module (24) to provide the final image pixel values
(47) of the second bit depth (M) as normalized, corrected image
data, said normalization module accumulating plural different
frames of the first bit depth (N) to calculate each final image
pixel value (47) of the second bit depth (M) to provide corrected
image data determined from accumulated different frames of the
first bit depth (N).
9. The system of claim 7, wherein the normalization module (24)
provides said normalized image data via said display image output
for use in said display module (16) to present a static X-ray image
from the high energy, real time, direct detection X-ray imaging
system (10).
10. The system of claim 9, wherein the normalization module (24)
accumulates said normalized image data over a period of time to
provide a high precision display image output for use in said
display module (16) to present said static X-ray image.
11. The system of claim 8, wherein the normalization module (24)
accumulates said normalized image data over a period of time of at
least one hundredth of a second to ten seconds for providing a high
precision display image output for each of the accumulation
periods, for use in said display module (16) to present said
dynamic X-ray image.
12. The system of claim 11, wherein the direct conversion radiation
detector substrate comprises a Cadmium Telluride composition based
radiation detector substrate (30) in communication with the ASIC
readout substrate (32).
13. The system of claim 12, wherein the radiation detector
substrate (30) consists of a composition selected from the group
consisting of: Cadmium-Telluride and Cadmium-Zinc-Telluride.
14. The system of claim 2, wherein the camera (37) includes a
detector substrate bias switch circuit (121).
15. The system of claim 4, wherein the high speed image frame
processing module (18) receives digitized pixel signals derived
from the output of each pixel circuit (31) of the readout substrate
(32) and uses the digitized pixel signals to generate an image
frame (44) at a frame readout rate of greater than 25 image frames
per second.
16. The system of claim 4, wherein the high speed image frame
processing module (18) receives digitized pixel signals derived
from the output from each pixel circuit (31) of the readout
substrate (32) and uses the digitized pixel signals to generate an
image frame (44) at a frame readout rate of greater than 50 image
frames per second.
17. The system of claim 4, wherein the software process includes a
calibration routine (20) which analyzes each of the digitized pixel
values (47) over at least some of the collected calibration frames
(44) being analyzed in accordance with a pixel value correction
algorithm (49) to provide and write pixel value correction data
specific to each pixel (36) in an image frame (44 ) to the lookup
table (22).
18. The system of claim 5, wherein the software driving the
calibration module (20) includes a pixel non-linear performance
compensation routine (123) providing error correction for each
pixel (36) as a function of time.
19. The system of claim 5, wherein the pixel non-linear performance
compensation routine (123) includes an asymmetric linear polynomial
calculation to determine correction coefficients to provide error
correction for each pixel (36) as a function of time.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a division of copending application Ser.
No. 11/226,877 filed on Sep. 14, 2005; which is a
continuation-in-part application Ser. No. 11/017,629 filed on Dec.
20, 2004; which claims the benefit of U.S. provisional application
Ser. No. 60/585,742 filed on Jul. 6, 2004 and claims the benefit of
priority to WO application PCT/IB05/01896 filed on Jul. 1, 2005.
The entire contents of each of the above-identified applications
are hereby incorporated by reference.
FIELD OF THE INVENTION
[0002] The present invention is in the field of semiconductor
imaging systems for imaging x-ray and gamma ray radiant energy.
More specifically, the invention relates to a high frame rate, high
energy charge-integrating imaging devices utilizing Cd--Te or
Cd--Zn--Te based detector substrates in combination with CMOS
readout substrates. Additionally, the invention relates to a
process for calibrating such high energy radiation imaging
systems.
BACKGROUND OF THE INVENTION
[0003] Over the past ten years digital radiation imaging has
gradually been replacing conventional radiation imaging for certain
applications. In conventional radiation imaging applications, the
detecting or recording means is a photosensitive film or an analog
device such as an Image Intensifier. Digital radiation imaging is
performed by converting radiation impinging on the imaging device
(or camera) to an electronic signal and subsequently digitizing the
electronic signal to produce a digital image.
[0004] Digital imaging systems for producing x-ray radiation images
currently exist. In some such devices, the impinging or incident
radiation is converted locally, within the semiconductor material
of the detector, into electrical charge which is then collected at
collection contacts/pixels, and then communicated as electronic
signals to signal processing circuits. The signal circuits perform
various functions, such as analog charge storing, amplification,
discrimination and digitization of the electronic signal for use to
produce an digital image representation of the impinging
radiation's field strength at the imaging device or camera. These
types of imaging systems are referred to as "direct radiation
detection" devices.
[0005] In other devices, the impinging radiation is first converted
into light in the optical or near optical part of the visible light
spectrum. The light is subsequently converted to an electronic
signal using photo detector diodes or the like, and the resultant
electronic signal is then digitized and used to produce a digital
image representation of the impinging radiation's field strength at
the imaging device or camera. This type of imaging system is
referred to as an "indirect radiation detection" device.
[0006] Currently, operation of a flat panel imaging device/camera
(of either the direct type or indirect type of detector) typically
involves collecting and integrating a pixel's charge over a period
of time and outputting the resultant analog signal which is then
digitized. Present charge integration times are typically from 100
msec to several seconds. Devices presently available in the field
are suitable for single exposure digital x/gamma-ray images, or for
slow multi-frame operation at rates of up to 10 fps (frames per
second). The digitization accuracy typically is only about 10 bits,
but can be 14 to 16 bits if the charge integration time is
sufficiently long. The high end of digitization accuracy currently
is accomplished in imaging systems wherein the typical charge
integration times range from several hundred milliseconds up to a
few seconds. Therefore, in these current imaging systems,
increasing accuracy requires increasing the pixel charge
integration time. Unfortunately, errors inherent in current imaging
systems limit the length of a charge integration cycle to just a
few seconds at most, before the signal-to-noise ratio first
"saturates" and then becomes so bad as to preclude any increase in
accuracy with increasing charge integration time.
[0007] In any event, it is the cumulative integrated analog signal
that is readout from the camera and digitized. Then calibration is
applied to correct the non-uniformities inherent in flat panel
imaging device, and more rarely to correct the non-linear behavior
of the imaging system itself.
[0008] Designing and manufacturing a sensitive, high energy
radiation-imaging device is a very complex task. All the device's
structural modules and performance features must be carefully
designed, validated, assembled and tested before a fully
functioning camera can be constructed. Although great progress has
been made in the research and development of semiconductor
radiation imaging devices, a large number of old performance issues
remain and certain new performance issues have developed. Some of
the new performance issues result from solving other even more
severe performance problems, while some are intrinsic to the
operating principle of such devices.
[0009] High energy "direct radiation detector" type x-ray imaging
systems typically utilize semiconductor detector substrate composed
of Cd--Te or Cd--Zn--Te compositions. The Cd--Te or the Cd--Zn--Te
detector substrate is typically bump-bonded to a CMOS readout
(signal processing) substrate. It can also be electronically
connected to the CMOS readout with the use of conductive adhesives
(see US Patent Publication No. 2003/0215056 to Vuorela). Each pixel
on the CMOS readout substrate integrates the charge generated from
the absorption the impinging x/gamma rays in the thickness of
material of the detector substrate. The known performance impacting
issues with Cd--Te or Cd--Zn--Te/CMOS based charge-integration
devices can be divided into two major areas: electrical performance
problems and materials/manufacturing defects. Electrical
performance problems can be further subdivided into six different
though partially overlapping problems: leakage current,
polarization or charge trapping, temporal variation, temperature
dependency, X-ray field non-uniformity, and spectrum dependency.
Materials/manufacturing defects problems can also be further
subdivided into: Cd--Te or Cd--Zn--Te detector material issues,
CMOS-ASIC production issues, and overall device manufacturing
issues.
[0010] The main reasons for use of crystalline compound
semiconductors such as CdTe and CdZnTe in the detector substrate of
a charge-integrating imaging device is their superb sensitivity,
excellent pixel resolution, and quick response (very little
afterglow) to incoming radiation. On the other hand, current
methods of producing Cd--Te and Cd--Zn--Te flat panel substrates
limits their uniformity and impacts the crystal defect rate of
these materials, which as can cause some of the problems mentioned
above. In addition, due to the use of an electric field of the
order of 100V/mm or higher, a considerable leakage current (or dark
current) results, causing image degradation.
[0011] Prior descriptions of Cd--Te or Cd--Zn--Te based x-ray/gamma
ray imaging devices exist. For example, U.S. Pat. No. 5,379,336 to
Kramer et al. and U.S. Pat. No. 5,812,191 to Orava et al. describe
generally the use of Cd--Te or Cd--Zn--Te semiconductor detector
substrates bump-bonded to ASICs substrates of a charge-integration
type digital imaging camera. However, these documents make no
mention of and do not address the issues arising when a device of
this type operates at high frame rates exceeding 10 fps, or how to
calibrate, or even the need to calibrate in the case of such an
application. Another example is European Patent EP0904655, which
describes an algorithm for correcting pixel values of a Cd--Te or
Cd--Zn--Te imaging device. However the issue of operating the
device at high rates and how to compose an image from many
uncorrected individual frames is not addressed. EP0904655 simply
provides a correction algorithm for correcting pixel values from a
single exposure and consequently displaying such pixel values.
[0012] Although these prior devices and methods may be useful each
for its intended purpose, it would be beneficial in the field to
have a high energy x-ray, real time imaging system that provides
both increased image frame readout rates of substantially greater
than 10 fps and greater than 16 bit accuracy. For example, it would
be useful in the fields of panoramic dental imaging, cephalometry,
and computerized tomography to have high energy X-ray imaging
systems with both increase frame readout rates and high accuracy.
Even static imaging applications, where the exposure time is a
multiple of the single frame duration, it would be useful to have
such an imaging system.
SUMMARY OF THE INVENTION
[0013] The present invention is a high energy, direct radiation
conversion, real time X-ray imaging system. More specifically, the
present real time X-ray imaging system is in tended for use with
Cd--Te and Cd--Zn--Te based cameras. The present invention is
particularly useful in X-ray imaging systems requiring high image
frame acquisitions rates in the presence of non linear pixel
performance such as the one encountered with CdTe and CdZnTe
pixilated radiation detectors bonded to CMOS readout. The present
invention is "high energy" in that it is intended for use with
X-ray and gamma ray radiation imaging systems having a field
strength of 1 Kev and greater. The high energy capability of the
present X-ray imaging system is derived from its utilization of
detector substrate compositions comprising Cadmium and Telluride
(e.g., Cd--Te and Cd--Zn--Te based radiation detector substrates)
in the imaging camera. Cd--Te and Cd--Zn--Te based detector
substrates define the present invention as being a direct radiation
conversion type detector, because the impinging radiation is
directly converted to electrical charge in the detector material
itself.
[0014] The detector substrate is a monolith and has a readout face
or surface which is highly pixelized, i.e., it has a high density
pattern of pixel charge collectors/electrodes on it. The pattern is
high density in that the pitch (distance from center-to-center) of
the pixel charge collectors is 0.5 mm or less. Each pixel's
collector/electrode is in electrical communication (e.g., via
electrical contacts such as bump-bonds or conductive adhesives) to
the input of a pixel readout ASIC ("Application Specific Integrated
Circuit") on the readout/signal processing substrate. The detector
substrate provides for directly converting incident x-rays or gamma
radiation to an electrical charge and for communicating the
electrical charge signals via the pixel electrical contact to the
readout ASIC. The readout/signal processing ASIC provides for
processing the electrical signal from its associated pixel as
necessary (e.g., digitizing, counting and/or storing the signal)
before sending it on for further conditioning and display. The
capability of the present invention to be read out at high frame
rates enables the real time imaging feature and secondly enables
image reconstruction (real time or static) from a plurality of
digitized individual frames. Real time imaging refers to the
capability of the system to generate image frames for display in
sufficiently rapid succession to provide a moving picture record in
which movement appears to occur substantially real time to the
human eye.
[0015] Descriptions of flat panel x-ray imaging cameras
substantially analogous to the intended Cd--Te or a Cd--Zn--Te
based charge-integrating detector bonded to an ASIC readout/signal
processing substrate are known in the art. Examples are disclosed
in US Patent Application Publication serial number 2003-0155516 to
Spartiotis et al. relating to a Radiation Imaging Device and
System, and US Patent Application Publication serial number
2003-0173523 to Vuorela relating to a Low Temperature, Bump-Bonded
Radiation Imaging Device, which documents are incorporated herein
by reference as if they had been set forth in their entirety.
[0016] In a preferred embodiment of the present imaging system, the
imaging device or camera is "readout" at a high frame rate. A high
frame rate as used herein means that the accumulation and
distribution of electrical charge developed in the detector
semiconductor substrate is utilized ("readout") to produce a
digital image frame at a rate greater than about 10 individual
image frames per second up to 50 and greater individual image
frames per second and in certain embodiments up to 300 frames per
second or more. An individual image frame is a digital
representation of the active area (pixel pattern) of the camera's
detector substrate. An image frame is generated each time the ASIC
substrate is readout. The digital representation can be described
as a matrix of digitized individual pixel signal values. That is,
each pixel value of each pixel in the image frame is a digitized
representation of the intensity of the electronic signal level
readout for the corresponding specific pixel on the detector
substrate.
[0017] In accordance with the invention, each pixel value in the
image frame includes an individual calibration correction specific
to that pixel value of the specific frame, and therefore in fact is
a corrected digital pixel value. The specific calibration
correction for each image pixel is derived from the present pixel
value correction calibration process. The individual corrected
digital pixel values of the same specific image pixel from
different image frames is processed according to an algorithm of
the calibration process over at least some of the collected image
frames to provide the pixel value to be displayed in the final
image. The final image can be a real time image or a static
digitally accumulated image.
[0018] A characteristic of the present invention is that the final
image to be displayed has pixel values with a bit depth that is
higher than the bit depth of pixels from individual frames. For
example, each frame may have a 12 bit resolution but when
accumulating several such frames to compose a real time or static
image the final pixel depth in the displayed image can indeed be
14, 16 or even 18 bits in real terms. This is a significant
advancement over the prior art because the extra bit resolution
docs not come at the expense of performance in other respects. For
example, in the prior art, in order to get 16 bits or more, one has
to integrate on the device (analog integration) for several hundred
milliseconds or even seconds. However, in doing so, one integrates
dark (or leakage) current and other types of noise as well. To
achieve the desired performance, it is of paramount importance that
the individual frames are calibrated and that pixel values of
individual frames be corrected with high precision. Therefore, it
is a further object of the present invention to provide such a
calibration (or correction) method to enable the current invention
to be implemented. The calibration method is applicable on each
pixel of the imaging system and takes into account the offset and
gain corrections as well as temporal (time) corrections as this is
applied on a frame by frame basis. There may be no need to have
different correction for each pixel and each frame hut, in
accordance with the current invention, at least some of the frames
have different temporal correction for corresponding pixels.
BRIEF DESCRIPTION OF THE DRAWINGS
[0019] FIG. 1a is a block diagram generally illustrating the
interconnect relationship of components of the present high energy,
direct radiation conversion, real time X-ray imaging system.
[0020] FIG. 1b is a schematic diagram of the X-ray imaging system
of the invention.
[0021] FIG. 2a is a schematic representation of an imaging device
useful in the camera module of the present invention.
[0022] FIG. 2b is a cross-sectional side view of the camera of the
invention.
[0023] FIG. 2c is a schematic view of the camera and/or frame of
the invention, made up of an array of image pixels.
[0024] FIG. 3a is a schematic representation of the static frame
accumulation method of the invention.
[0025] FIG. 3b is a schematic representation of the shift-and-add
method of the invention.
[0026] FIG. 3c is a graph of the measured pixel response compared
with the ideal pixel response.
[0027] FIG. 4a is a graphic representation of the output over time
of a single pixel circuit of a Cd--Te based direct conversion
camera using detector bias voltage switching. The figure
illustrates that the output signal from a typical pixel circuit
drifts over time as circuit recovers from a bias voltage switching
event (pulse).
[0028] FIG. 4b is a schematic of the detector substrate bias
switching circuit used in the invention.
[0029] FIG. 5 is a graph illustrating the temporal variation in the
raw intensity value of the same single image pixel of FIG. 4a
overlaid with a series of image frame capture points generated over
time after a bias voltage switching event.
[0030] FIG. 6 is a graph illustrating normalization of the
intensity value of an image pixel by the application of a specific
time dependent correction coefficient to the raw intensity value of
the particular image pixel's output in each image frame.
[0031] FIG. 7 is a graph illustrating an asymmetric data sampling
feature of the calibration procedure of the present imaging system
for ameliorating the problem of excessive data collection and
processing load.
[0032] FIG. 8 is a simple block diagram of the calibration
procedure of the invention.
[0033] FIG. 9 is a block flow chart illustrating a general overview
of the present calibration procedure.
[0034] FIG. 10 is a block flow diagram illustrating a data
collection strategy from a single pixel circuit at a specific
reference X-ray field intensity.
[0035] FIG. 11 is a block flow diagram illustrating a strategy for
calculating correction coefficients for each image pixel in a pixel
frame.
[0036] FIG. 12 is a block flow diagram illustrating a strategy for
detecting and compensating for bad or uncorrectable pixels.
[0037] FIG. 13 is a block flow diagram illustrating the application
of the present calibration process to provide a normalize image
frame.
[0038] FIG. 14a is a graph illustrating the typical prior uniform
sampling method wherein a piece-wise constant function is used to
determine correction coefficient for normalizing pixel intensity
values at specific times or intensities to fit a curve.
[0039] FIG. 14b is a graph illustrating a non-uniform sampling
method wherein a piece-wise constant function is used to determine
correction coefficients for normalizing pixel intensity values at
specific times.
[0040] FIG. 14c is a graph illustrating an alternative
(non-uniform) sampling method wherein a piece-wise linear function
is used to determine correction coefficients for normalizing pixel
intensity values at specific times.
DETAILED DESCRIPTION OF THE INVENTION
[0041] Referring now to the drawings, the details of preferred
embodiments of the present invention are graphically and
schematically illustrated. Like elements in the drawings are
represented by like numbers, and any similar elements are
represented by like numbers with a different lower case letter
suffix. As illustrated in FIG. 1a and 2b, the present invention is
a high energy, real-time capable, direct radiation conversion X-ray
imaging system 10. More specifically, the present invention relates
to such X-ray imaging systems 10 utilizing a Cd--Te or Cd--Zn--Te
based camera. The present real-time capable X-ray imaging system
10, like imaging systems generally, comprises a camera module, an
image processor 14, and a display means 16. In the present
real-time X-ray imaging system 10, the camera module 12 includes an
X-ray imaging device 28 having a Cd--Te or Cd--Zn--Te based
radiation detector substrate 30 in electrical communication with an
Application Specific Integrated Circuit (ASIC) readout substrate
32. Each active pixel 36 on the detector 30 is electrically
connected to a corresponding pixel circuit 31 on the ASIC readout
substrate 32.
[0042] Referring now to FIG. 1b, the system 10 includes a PC 76, in
which a frame grabber 78 and imaging software 80 operate, connected
via a camera link 82 to the X-ray unit 84, including a camera 37,
power supply 86, and ac/dc adapter 88. The X-ray unit 84 generally
further includes network connections 90 for connecting to the PC or
terminals in a network, for example.
[0043] Referring now to FIG. 2a, the camera 37 has an interface
printed circuit board (PCB) 92 connected via a databus 94 to a
Detector PCB 96 and having a cooling element 98.
[0044] The x-ray imaging device 28 is capable of producing multiple
image frames 44. Each frame 44 is made up of an array 45 of
un-corrected image pixel values.
[0045] Referring now to FIG. 2b, a schematic representation of an
imaging device 28 useful in the camera module 12 of the present
imaging system 10 is shown. In these imaging devices 28 as
generally exemplified in FIG. 2, the detector semiconductor
substrate 30 has electrically connections 35 to an readout ASIC
substrate 32 (e.g., bump-bonds in the preferred embodiment
illustrated). The detector material 34, a Cadmium-Telluride or
Cadmium Zinc Telluride based composition in the present invention,
of the semiconductor substrate 30 absorbs incoming radiation, and
in response to the absorption the radiation energy is directly
converted to electrical charges within the thickness of the
detector material 34. The electrical charges are collected at the
detector pixel's collection electrode (pixel contact) 38 of each
active or functioning pixel 36, and electrically communicated
through the electrical connections 35 to the pixel circuit contacts
33 on the pixel circuit 31 of the readout ASIC substrate 32. The
electric charge signals are stored and/or processed at a detector
pixel's corresponding pixel circuit 31 on the readout ASIC 32.
Thereafter, the ASIC pixel circuits 31 are usually multiplexed and
an analog output is sequenced and digitized either on chip or
off-chip. In accordance with the invention, each pixel value 36 in
an image frame 44 is digitized and additionally includes an
individual calibration correction specific to that pixel value of
the specific frame, and therefore in fact is a corrected digital
pixel value. The specific calibration correction for each image
pixel 47 is derived from a plurality of individual single frame
pixel values 36 corrected according to a correction calibration
process. The individual corrected digital pixel values 36 of the
same specific image pixel 47 from different image frames 44 are
processed according to an algorithm of the normalization module 24
over at least some of the collected image frames 44 to provide the
pixel value to be displayed in the final image. The final image can
be a real time image or a static digitally accumulated image.
[0046] Referring now to FIG. 2c, the imaging device 28 of the
invention is capable of producing multiple image frames 44, each
frame including an array 45 of frame pixel values 36, with a
certain bit depth (i.e. the color or gray scale of an individual
pixel--a pixel with 8 bits per color gives a 24 bit image, because
8 Bits.times.3 colors is 24 bits--e.g., 24 bit color resolution is
16.7 million colors). The system 10 includes processing means 24
for calculating image pixel values 47 from pixel values 36 of
different frames 44, wherein the bit depth of the image pixel
values 47 is greater than the bit depth of the pixel values 36 from
the individual frames 44. By way of example, single frame
digitization may be for example only 12 bits, or 0 to 4096,
maximum. Such analog to digital converters (ADC's) are quite common
and inexpensive today. Additionally, they can be quite fast and
operate with clock rates of 5 MHz or even 10 MHz-20 MHz. A typical
CdTe-CMOS camera as implemented by the assignee of the current
invention may comprise 10 k pixels to 1M pixels. This means that
frame rates of 20 fps-300 fps or even up to 2,000 fps can be
achieved with a single ADC. After the frames 44 are read out,
un-corrected pixel values are digitized and, consequently, in
accordance with the present invention, a correction, calculated
using a pixel correction algorithm 20, is applied to the digital
pixel values to obtain corrected frame digital pixel values 36 from
single frames. Then, as depicted in FIG. 3a, digital corrected
pixel values 36 from different frames 44 can be accumulated to
yield digital corrected pixel values 47 of an image to be displayed
with a bit resolution far greater than the 12 bits. For example,
with 17 frames of 12 bit resolution, each one can become more than
16 bit after digital accumulation (17.times.4096=69632>16 bits).
This indeed is a breakthrough in digital x-ray imaging because such
resolutions were previously achievable at the expense of long
integration times and the use of 16 bit ADC's that are very
expensive and very slow, thus inhibiting real time image display.
Additionally, as was explained and will be explained further, long
integration times of the analog signal cause other problems such as
an increase of the dark current and other types of noise.
[0047] Referring now to FIG. 3b, corrected digital pixel values 36
combined from different frames 44 can be corresponding pixel values
or can be from different positions in the frame 44 (such as in the
case of scanning). In essence, the system 10 includes a method 20,
49, for correcting the image pixel values from different image
frames 44, and a processing method 24 for calculating corrected
pixel values 47 of an image, the method utilizing corrected digital
pixel values which correspond in a broad sense, from several
frames.
[0048] As mentioned, the current invention 10 comprises preferably
a CdTe or CdZnTe based x-ray/gamma-ray imaging device 28 whereby
the CdTe/CdZnTe pixilated detector substrate or substrates 30
is/are bump-bonded to at least one readout ASIC 32, the CdTe/CdZnTe
detector substrate provided for directly converting impinging
x-rays or gamma rays to an electronic signal and the readout ASIC
provided for storing and/or processing the electronic signal from
each pixel 36 and consequently reading out the signal. The
CdTe/CdZnTe imaging device 28 is read out at a high frame rate of
preferably 10 individual frames per second, or even more preferably
25 fps-100 fps and in some cases up to 300 fps or more. The
individual frames 44 are being digitized so that each frame is a
string of pixel values 36, each pixel value corresponding to a
digitized signal level for a specific pixel 36 in the frame that
was produced by the device 28. The digitized pixel values for each
frame 44 are being corrected in accordance with a pixel correction
algorithm 49 already described hereafter. The individual corrected
digital pixel values 36 of different frames 44 corresponding to the
same pixel 36 are digitally added or averaged or processed
according to an algorithm over at least some of the collected
frames to provide a pixel value 47 to be displayed in the final
image.
[0049] Critical to the invention is the actual implementation of
the correction of the digital pixel values from each individual
frame 44 which has to take into account all the deficiencies of the
CdTe or CdZnTe crystals, CMOS non-linearity and offsets, dark
current, polarization and other effects which will be subsequently
explained. In the next section, real time, efficient pixel
correction is described. Different correction and/or calibration
techniques may be used in the present invention, without changing
the scope or diverting from the invention.
[0050] The camera module 12 and the high speed frame processor
module 18 are in communication via a cable link 60. The camera
module 12 provides processed and organized pixel data, representing
the individual raw pixel circuit output of each pixel 36 (or pixel
cell 29), to the frame processor module 18. The high speed frame
processor module 18 includes a circuit for the frame grabber 78
(optionally frame grabber 78 may also he part of the camera module
12), typical in the field, which captures the pixel circuit data
from the camera module 12 further processes the pixel circuit data
to provide a raw time-stamped image frame representing the raw
pixel circuit output of each pixel cell 29. The frame processor
then communicates the raw time-stamped image frame data via a frame
data link 66 to the calibration module 20 if the system 10 is in
the calibration mode, or otherwise to the normalization module
24.
[0051] The calibration module 20 controls the calibration process
49. The calibration process 49 analyzes the raw time-stamped image
frame data and other calibration parameters, such as reference
field radiation intensity, and generates the data necessary to load
the look-up table of the calibration data structure module 22. The
calibration module 20 writes to the data structure via a database
link 68. Without proper calibration data loaded into the look-up
table, any image output from the normalization module 24 to the
display module will be inaccurate. Therefore, the calibration
process 49 must be run prior to normal imaging operation of the
present system 10.
[0052] When not in calibration mode, the frame processor 18
communicated the time-stamped data of the image frame 44 to the
normalization module 24. The normalization module 24 operates on
each image pixel of the raw time-stamped image frame with the image
pixel's corresponding correction requirement derived from the
look-up table via a second database link 70. The normalization
module 24 then provides a normalized image frame to the display
module 16 via a display data link 74. Every image pixel of the
normalized image frame represents its corresponding raw image pixel
intensity value corrected by it corresponding correction
coefficient from the look-up table.
[0053] To obtain a high quality image, several obstacles need to be
overcome in relation to Cadmium-Telluride based detector substrates
30. For example, there is a continuous leakage current (aka: dark
current) that must be compensated for. Certain Cd--Te or Cd--Zn--Te
detector materials 34 are manufactured having a blocking contact
(not shown) to control the level of leakage current. Other
manufactures have various amounts of Zn or other dopants in the
detector material 34 to suppress leakage current. In any event the
leakage current creates noise and also fills up the charge
collection gates 33 on each pixel circuit 31. Additionally the use
of blocking contacts introduces the problem of polarization or
charge trapping which becomes evident after few seconds of
operation, for example, after 5 sec, 10 sec or 60 seconds etc.,
depending on the device.
[0054] The advantage of using Cadmium-Telluride based compositions
(i.e., Cd--Te and Cd--Zn--Te) as the radiation absorption medium 34
in the present detector substrate 30 is their very high radiation
absorption efficiency, minimal afterglow and their potential for
high image resolution. Therefore, it is valuable to have imaging
systems that mitigate or eliminate the above issues. Even in the
absence of a blocking contact the issue of the leakage current and
crystal defects do not allow long exposures in excess of 100 msec
without increasing the size of the charge storage capacitor on each
pixel circuit 31 of the ASIC readout substrate 32. However, this
would be to the detriment of sensitivity, because the larger the
charge storage capacitance is, the lower the sensitivity becomes.
For example, the present invention has been successfully practiced
using a capacitance of the order 50 F as charge storage capacitance
on each ASIC pixel circuit receiving charge. With this size of
capacitance, the practical maximum exposure time given the Cd--Te
or Cd--Zn--Te leakage current and other defects would be 100 msec
or less.
[0055] Referring now to FIGS. 4a and 4b, a very useful mechanism
for preventing excessive polarization (charge trapping) from
forming in a direct conversion (charge coupled) radiation detector
device is to briefly cycle the high voltage bias off and on, a
technique called the detector bias voltage switching technique, in
which the detector substrate bias voltage is switched off for a
brief period (less than 100 milliseconds) at the end of a data
collection cycle. The duration of a data collection cycle is
selectable, e.g., from every three to twenty or more seconds. Bias
voltage switching prevents polarization or charge trapping from
developing in the detector substrate 30. However, the bias voltage
switching technique is new in the field of X-ray imaging systems,
and does have certain aspects that can impact image quality if
these are not addressed. One such aspect is "dead-time," and the
other is "pixel response drift." "Dead-time" is the period in a
data collection cycle when the detector bias voltage is off and no
detector charges can be collected. "Pixel response drift" is the
result of switching the detector bias voltage back on, and is the
initial period that the data collection cycle that the pixel's
response to a static radiation field has not yet stabilized. Both
of these limitations are illustrated in FIG. 4a. The detector
substrate bias switching circuit 121 is shown in FIG. 4b.
[0056] For the purpose of the embodiment illustrated in FIG. 4a,
the data collection cycle time Ct was the time between the
initiation of detector bias voltage off/on pulses 50. The dead-time
Dt consists of the actual high voltage down-time Vo plus some
stabilization time after the high voltage has been switched back
on. The effect of dead-time Dt cannot be less than Vo, and hence
cannot be completely eliminated in a switched detector bias voltage
imaging system. However, it can be minimized in part by reducing
the off-time of the bias voltage to as short a period as is
appropriate to allow any polarization (trapped charge) to bleed off
and/or to keep the dead-time to a negligibly small portion of the
data collection cycle.
[0057] The other potentially limiting aspect of a bias voltage
switched detector is pixel response drift Rd, which relates to the
non-linear aspect of a pixel circuit's output signal over time 40
in response to a static radiation field exposure level (See FIG.
4a). This non-linearity is most pronounced immediately following
the voltage-on step of the voltage off-on pulse 50. Uncorrected,
this non-linearity causes pumping of the image's overall brightness
level in a real time image display. The pixel cell non-linear
response in a switched bias voltage imaging device is an excellent
case for applying the post-image frame generation calibration
method of the present imaging system to eliminate this intensity
distortion of a real time X-ray image display.
[0058] Referring now to FIG. 9, the present calibration method 49
collects calibration data for the complete data collection cycle at
a number of different homogeneous reference radiation field
intensities, including a dark current intensity. Thus, the method
49 is especially useful for practice in digital imaging systems
utilizing detector bias voltage switching. The camera module 12 of
a digital imaging system utilizing detector bias voltage switching
typically comprises a detector/ASIC assembly 28 having thousands of
pixel cells 29, each comprising a detector pixel 36 and an
associated pixel circuit 31. Each pixel circuit 31 includes
associated circuitry and a pixel circuit signal output (not shown)
producing a digitized pixel signal for that pixel circuit 31. A
pixel circuit output signal indicates the intensity of the
X-ray/Gamma ray radiation energy impinging on the associated
detector pixel 36. See FIG. 2b. Further, for each reference
intensity, the cycle is repeated to reduce random noise.
[0059] The collected digitized pixel signal outputs are
communicated via a camera link 60 to a high speed frame processor
module 18 of the image processor 14. The frame processor module 18
includes a frame grabber circuit which receives the individual
pixel circuit output signals from each pixel circuit 31. The frame
processor module organizes the individual digitized pixel signals
into an image frame, with each image pixel of the image frame
representing the pixel signal of a corresponding to the pixel
circuit in the imaging device 28 of the camera module 12. The
intensity of an image pixel in the image frame is representative of
the strength of the pixel signal received from the corresponding
pixel circuit 31. However, because of the inherent differences in
the mechanical and electrical properties of the individual
constituents of each pixel cell 29, the intensity response of the
various pixels comprising an image frame are not uniform, even in
response to a uniform x-ray field. Therefore, calibration of the
imaging system is necessary before the information represented by
the image frame is useful to a user.
The Calibration Procedure
[0060] Referring now to FIG. 8, a very high level flow chart of the
calibration procedure 49 is shown, including the input of a pixel
value 36 into a correction function 110, in which a correction
coefficient 120 is applied, to yield a corrected pixel value 47.
FIG. 9 is a more detailed overview of the steps of the calibration
process 49 of the present imaging system 10. Calibration data is
collected for the complete data collection cycle at a number of
different homogeneous reference radiation field intensities,
including a dark current intensity I.sub.D. In a first step 49a,
data is collected for dark current I.sub.D. In a second step 49b,
data is collected for X-ray intensity I.sub.I. In a third step 49c,
data is collected for X-ray intensity I.sub.N. In a fourth step
49d, correction coefficients are calculated and the look-up table
22 written to.
[0061] Referring now to FIGS. 10 to 12, the calibration procedure
49 is described in still further detail. In FIG. 10, the data
collection cycle submethod 120a is described. In a first step 122,
the Data Bins are initialized, such bins having a structure as
follows:
[0062] Bin 1: Time 0 . . . T.sub.1
[0063] Bin 2: Time T.sub.1 . . . T.sub.2
[0064] Bin N: Time T.sub.N-1 . . . T.sub.N.
[0065] In a second step 124, the radiation field intensity is set.
In a third step 126, high voltage is pulsed. In a fourth step 130,
the timer is reset. In a fifth step 132, the collect time is set to
equal the time of the image frame, T.sub.IF, and a loop, which
continues as long as the cycle is still active, the data bin B is
found and the frame 44 is added to the bin. Then, in a seventh step
134, if there are more repetitions to be performed, in order to
reduce noise, for example, the loop is run again.
[0066] In FIG. 11, the submethod 120 for calculation of correction
coefficients includes the following steps. In a loop 140 over each
bin and, within that loop, a loop 142 over each pixel 36, in a
first step 144, a polynomial is fit to all intensity values I.sub.D
and I.sub.O . . . I.sub.N and, if the pixel fails a threshold test,
the pixel 36 is flagged. In a second step 146, the data structure
(look up table), is written to. In a third step 148, the submethod
120b continues to a masking routine 150.
[0067] In FIG. 12, the masking submethod 150 includes the following
steps. In a first step 152, the submethod 150 checks for flagged
pixels 36. For each flagged pixel 36, in a second step 154, the
submethod 150 finds good neighboring pixels 36. In a third step
156, the good neighboring pixel locations are written to the data
structure 20. When there are no flagged pixels 36 remaining, the
submethod 150 ends.
[0068] In FIG. 13, the normalization procedure 160 is described,
including the following steps, performed on the raw image pixel
data from the frame processor module. In a first step 162, during
operation of the system 10, the image frame 44 is received and time
stamp is set to "T". In a second step 164, the bin is found for
time "T". In a third step 166, looping over each pixel 36, the
pixel is checked to see if it's flagged or bad. If yes, then, in a
fourth step 168, the pixel value 47 is replaced with a weighted
mean value of good neighbors. In a fourth step 170, any correction
polynomials are applied.
[0069] The raw image pixel data from the frame processor module The
calibration process uses a software driven calibration module 20 to
create and maintain a "look-up table" resident in a data structure
module 22. The look-up table is a set of time dependent, image
pixel specific correction coefficients 54 for each pixel of an
image frame. The pixel specific correction values 54 are referenced
to a target uniform intensity value 52 (see FIG. 5), and are used
to correct the raw value of the specific image pixel to a
normalized value. Therefore, each image pixel represented in an
image frame has a data set of time dependent correction
coefficients in the look-up table of the data structure module 22
generated for each of a number of reference x-ray field
intensities.
[0070] The time dependency of a set of correction
coefficients/values derives from the application of a time-stamp to
each image frame processed by the high speed frame module. The
time-stamp indicates the time elapsed since the start of the data
collection cycle Ct that the image frame 44 was generated. In the
preferred embodiment illustrated in FIG. 5, the image frames 44
that are time-stamped were captured (grabbed) from the camera
module 12 at uniform frame intervals 46 in the data collection
cycle Ct. Therefore, the image frames 44 that are time-stamped
always had the same time difference relative to each other. The
first frame grabbed after detector bias voltage was switched on was
assigned time-stamp=0, second had time-stamp=1, and so on up to
time-stamp=N. In practice, a separate calibration data set was
calculated for each image pixel and included a correction value for
that specific image pixel at each time-stamp in the data collection
cycle Ct. Alternatively, the calibration data can be thought of or
organized as consisting of N different calibration data sets, one
for each image frame of the data collection cycle Ct, each frame
data set comprising a separate correction value/coefficient for
each image pixel in the frame. For best image quality, N should be
selected as the highest number of different time stamps possible
N.sub.max, or in other words, the highest frame rate possible.
However, this would be an extremely data intensive condition and
due to current limitations in the technology, e.g., limited
computer memory processing times, an N<N.sub.max has to be
selected.
[0071] Referring now to FIG. 6 is a graph 186 illustrates
normalization of the intensity value of an image pixel 47 by the
application of a specific time dependent correction coefficient to
the raw intensity value of the particular image pixel's output in
each image frame 44.
[0072] Collecting the data. First step in the calibration method is
to collect the relevant data, specifically, the response of the
camera's imaging device 28 to different reference radiation field
intensities. The response of each pixel cell 29 of the device 28 is
collected for all the time-stamps in the data collection cycle Ct.
In the preferred embodiment illustrated, this step was repeated for
one or more times (generally 20 or more), to reduce the effect of
incoming quantum noise. Collecting the relevant data this way
corrects for any non-uniformities in the detector or ASIC
components, but also intrinsically provides "flat-field"
correction. In this embodiment, the calibration method tied the
imaging device 28 of the camera module 12 to a specific geometric
relationship with the radiation source. Which is to say that
calibration had to be redone whenever the radiation source or the
geometry between the imaging device 28 and the radiation source was
changed. Also, calibration should was repeated for each radiation
spectrum used.
[0073] Calculation of Pixel Specific Correction
Coefficients/Values. The response of a single pixel cell 29 as a
function of time and with exposure to different reference radiation
field intensities has a characteristic shape. The basic idea behind
the present calibration method is uniformity. Each and every pixel
cell 29 should give the same pixel output signal if exposed to the
same intensity of radiation. This means that the calibration
function
y.sub.out=f.sub.pix(x.sub.in) (1)
is a mapping from pixel output values x.sub.in to global output
values y.sub.out. The task is to find suitable functions f.sub.pix(
) for each pixel that gives the same output as all the other
pixels.
[0074] The choice to use polynomials was made because they are
extremely fast to calculate, which was absolutely necessary for
real-time operation. The polynomials are not the best basis for
regression problems like this, because of their unexpected
interpolation and extrapolation behavior. The function f.sub.pix( )
can now be explicitly written as:
y out = i = 0 M a i , pix x in i ( 2 ) ##EQU00001##
where a.sub.i,pix are the coefficients for pixel pix and M is the
order of the polynomial. The commonly used linear calibration (gain
and offset correction) is a special case when M=1. Use of up to
3.sup.rd order polynomial was the basis of the current embodiment,
but linear correction might be sufficient if a large enough number
of time-dependent coefficient datasets is used.
[0075] Estimating calibration parameters. A common way of
estimating model parameters in a regression problem like this is to
use a Maximum Likelihood (ML) estimation. This means that we
maximize the likelihood of all the data points for a one pixel at a
time given the function and noise model. Assuming normally
distributed zero-mean noise, the probability of one data sample
x.sub.1 is:
p ( x i | .sigma. , f ) = 1 2 .pi. .sigma. 2 Exp ( - ( x - f ( x )
) 2 .sigma. 2 ) ( 3 ) ##EQU00002##
and the total likelihood for all the samples assuming they are
statistically independent is:
LL = i = 1 N data p ( x i | .sigma. , f ) = ( 1 2 .pi. .sigma. 2 )
N data Exp ( - i = 1 N data ( x - f ( x ) ) 2 .sigma. 2 ) ( 4 )
##EQU00003##
[0076] A problem with Maximum Likelihood estimation is that it is
very difficult to apply any prior knowledge accurately. To overcome
this, a Maximum A Posteriori (MAP) estimation is used. In a MAP
estimation, the posteriori distribution of all the samples is
maximized by:
p ( .LAMBDA. , f | x ) = p ( x | .LAMBDA. , f ) p ( f ) p ( x ) ( 5
) ##EQU00004##
where .LAMBDA. is the estimated covariance matrix of samples
assuming independence, .LAMBDA.=diag[.sigma..sub.1 . . .
.sigma..sub.Ndata], x=[x.sub.1 . . . x.sub.Ndata] is the vector of
data samples and f=[f(x.sub.1) . . . f(x.sub.Ndata)] is the vector
of calibrated values for this pixel. p(x) is the uninteresting
scaling factor, evidence. If we assume normal distribution for
noise and for function parameter prior
p ( x | .LAMBDA. , f ) = ( 2 .pi. ) - N data 2 .LAMBDA. - 1 2 exp (
- 1 2 x T .LAMBDA. - 1 x ) ( 6 ) p ( f ) = ( 2 .pi. ) - M + 1 2
.sigma. prior 2 exp ( - 1 2 .sigma. prior 2 i = 0 M a i 2 ) ( 7 )
##EQU00005##
then the final posteriori will have form of:
p ( .LAMBDA. , f | x ) = ( 2 .pi. ) - N data 2 .LAMBDA. - 1 2 exp (
- 1 2 x T .LAMBDA. - 1 x ) ( 2 .pi. ) - M + 1 2 .sigma. prior 2 exp
( - 1 2 .sigma. prior 2 i = 0 M a i 2 ) p ( x ) ( 8 )
##EQU00006##
[0077] If we take the natural logarithm of the formula above and
group all the constant coefficients to new ones, we will get a cost
function of:
Cost = i = 1 N data 1 .sigma. i 2 ( x i - f ( x i ) ) 2 + .sigma.
prior 2 i = 0 M a i 2 ( 9 ) ##EQU00007##
which can be interpreted as a weighted and constrained linear least
squares cost function with penalty parameter of
.sigma..sub.prior.sup.2. The final parameter values can be solved
by differentiating the equation above with respect to all the
function parameters a.sub.1 and then setting the derivative equal
to zero. The motivation for using weighted least squares is that
when using different X-ray intensities, the quantum noise for the
highest intensity is much higher than for example the dark current.
This allows more weight to be given to smaller values, which are
probably more accurate.
[0078] Implementation and Performance Considerations. To optimize
image quality, 32-bit floating-point arithmetic was used in all the
calculations. Current x86 processors offer good SIMD (single
instruction, multiple data) command that allowed very efficient
parallel processing.
[0079] Selecting Appropriate Time-Stamped Calibration Image Frames
for Use in the Correction Protocol. For practical reasons, every
time-stamp in the data collection cycle Ct cannot be used because
the amount of data generated would be huge, and processing time and
memory allocations prohibitive in certain circumstances. This is
because current large-area cameras offer images up to 508.times.512
pixels. There are up to 4 parameters per pixel (if 3.sup.rd order
polynomial is used) and each parameter is 4 bytes. This means there
are 3.97 MB of data collected per frame. In the current embodiment,
the camera provided 50 frames per second, which meant a data
collection rate of 198 MB/second. In addition to this, the images
were read over the PCI bus in 16-bit format (24.8 MB/second) and
stored in the memory (another 24.8 MB/second). So the total data
rate for 50 fps operation was 248 MB/second. In frame averaging
mode, the previous image values were also read from the memory,
which gave another 24.8 MB/second, and a total of 273 MB/second
memory bandwidth. If the images are displayed on a screen, the
16-bit pixel values is read from the memory, a 32-bit color value
is read from the lookup-table per pixel and the final 32-bit values
is stored in the display memory giving additional 124 MB/second for
a grand total of 397 MB/second. And the field is moving to even
larger cameras.
[0080] If a first order model is used, one pixel requires at least
two 32-bit floating point numbers/frame. For a data collection
cycle time of 30 second, at a frame rate of 300 fps and a 96000
pixel image frame would mean 6.4 GB of data generated over a single
data collection cycle. FIGS. 12A to 12C are a further illustration
of this. FIG. 14a shows the prior art method of error sampling,
known as Uniform Sampling, at 300 fps, 30 sec cycle, 100,000
pixels, 4 parameters, 4 bytes/parameter, where we have a 3.sup.rd
Order polynomial for signal and a 0.sup.th order for time. However,
at 300 fps with a 30 sec data collection cycle and a 100,000 pixel
camera, and 4 parameters at 4 bytes/parameter, 13 GB of data must
be collected and processed. This is impractical. FIG. 14b shows a
present non-uniform method of error sampling, 0.sup.th order
interpolation, 300 data sets, 4 parameters, which under camera
operating perimeters similar to FIG. 14a only generated about 480
MB of data to be collected and processed. This is a reduction in
storage and processing requirements by a factor of 30 over the
prior art. Note that there are artifacts in the beginning and at
the end of the cycle. FIG. 14c illustrates a preferred non-uniform
error sampling method using linear interpolation, for 10 data sets,
4 parameters. Under camera operating parameters similar to FIG.
14a, this method only generated about 16 MB of data to be collected
and processed. This is a reduction in storage and processing
requirements by a factor of 30 over the prior art method of FIG.
14a. Note that there are small artifacts in the beginning and at
the end of the cycle. Bilinear correction was linear for signal and
linear for time. Linear interpolation in time reduces apparent
signal non-linearity and thus linear correction for signal is
adequate.
[0081] As shown in FIGS. 7 and 14c, a selection can be made to
utilize an optimized subset image frames, which the present
calibration does. At the beginning of the data collection cycle Ct,
the changes in a pixel cell's circuit output signal over time 40
are more drastic. Because of this greater variability, the
calibration data sets should include more relatively reference
frames from this portion of the collection cycle Ct than towards
the end of the collection cycle Ct where the output signal over
time 40 can be relatively flatter. In a preferred embodiment, an
automatic method was used to allow the user to change exposure time
(i.e. frame rate) and/or the off-time of the detector bias voltage
50, but the settings can be accomplished manually as well. Note
that in the graph shown, one bar represents one set of calibration
values.
[0082] How to Select Which Pixels to Mask. Some of the pixels cells
29 in an imaging device 28 are practically useless because of
material and manufacturing defects. Therefore, these pixels cells
29 have to be identified and masked out, i.e., each of their
outputs replaced with some reasonable value calculated from the
neighboring pixel cells 29. The present calibration method
calculates a local average value of a set of neighboring pixel cell
output signals and then compares this value to individual pixel
output signal values. This allows the calibration method to adapt
to a non-stationary radiation field. A preferred embodiment,
calculated an average frame at least 5 complete data collection
cycles at a single reference radiation field intensity setting.
This provided a very robust and dependable determination in minimal
time of the bad pixels cells 29 in an imaging device 28.
[0083] Calculating Replacement Values. After all the bad pixel
cells 29 have been located, their values are replaced with their
local arithmetic averages. There for the output signal of a
solitary bad pixel cell 29 is replaced with the average of four
good adjacent pixel output signals. The pixel output signal from
the bad pixel cell 29 is excluded in this calculation. The four
good adjacent pixel cells 29 were selected so that all the possible
directions were equally weighted. For example, if the pixel cell 29
above a first had pixel cell 29 is also a bad, then either the
pixel cell 29 to up-left or up-right is used instead in calculating
the replacement value for the pixel output signal of the first bad
pixel cell 29.
[0084] Geometry Correction and Filling-in Inactive Zones. The
relative positions on the ASIC hybrids are ideally close and
uniform, which means that there are some inactive areas (dead
space) between adjacent hybrids and that the relative distances can
vary between different adjacent hybrid. The solution to this
problem is two-step. First measurements were made of the distances
between hybrids and possible rotation angles of hybrids based on a
calibration image of a reference object. Then, the errors were
corrected based on these measurements. The measurements were made
by using the camera itself as a measuring device, and taking images
with a calibrated reference object that has very accurate
dimensions. Then after measuring the distances, the known and
measured values were compared and the mismatches detected.
[0085] Correction for Mismatches and Filling. After the exact
positioning of the hybrids was known, a correction algorithm was
implemented. Based on the distances a grid was constructed which
showed exactly where a given pixel should lie in the image. Based
on this, a bilinear interpolation (or any other interpolation
method) method was used to get the sub-pixel translated and rotated
new pixel values.
[0086] Multiple variations and modifications are possible in the
embodiments of the invention described here. Although certain
illustrative embodiments of the invention have been shown and
described here, a wide range of modifications, changes, and
substitutions is contemplated in the foregoing disclosure. In some
instances, some features of the present invention may be employed
without a corresponding use of the other features. Accordingly, it
is appropriate that the foregoing description be construed broadly
and understood as being given by way of illustration and example
only, the spirit and scope of the invention being limited only by
the appended claims.
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