U.S. patent application number 16/016215 was filed with the patent office on 2019-12-26 for photon scatter imaging.
The applicant listed for this patent is KROMEK GROUP, PLC. Invention is credited to James William Hugg, Ian Radley.
Application Number | 20190391282 16/016215 |
Document ID | / |
Family ID | 66998104 |
Filed Date | 2019-12-26 |
United States Patent
Application |
20190391282 |
Kind Code |
A1 |
Hugg; James William ; et
al. |
December 26, 2019 |
PHOTON SCATTER IMAGING
Abstract
One embodiment provides a method, including: receiving a dataset
associated with a plurality of photon emission events interacting
with a detector array of an imaging device; identifying a first
subset of the dataset associated with a plurality of unscattered
photon emission events from the plurality of photon emission
events; identifying a second subset of the dataset associated with
at least one scattered photon event from the plurality of photon
emission events; determining, for a scattered photon event, a
likely location of emission of the scattered photon event using
data from the first subset of the dataset associated with the
plurality of unscattered photon events; and correcting the dataset
by associating the scattered photon event with the determined
likely location of emission. Other aspects are described and
claimed.
Inventors: |
Hugg; James William; (Mars,
PA) ; Radley; Ian; (Durham, GB) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
KROMEK GROUP, PLC |
Sedgefield |
|
GB |
|
|
Family ID: |
66998104 |
Appl. No.: |
16/016215 |
Filed: |
June 22, 2018 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 6/0487 20200801;
A61B 6/4241 20130101; G01T 1/249 20130101; A61B 6/037 20130101;
G01T 1/247 20130101; A61B 6/502 20130101; G01T 1/1647 20130101;
A61B 6/485 20130101; G01T 1/2985 20130101; A61B 6/4258
20130101 |
International
Class: |
G01T 1/24 20060101
G01T001/24; A61B 6/03 20060101 A61B006/03; A61B 6/00 20060101
A61B006/00; A61B 6/04 20060101 A61B006/04 |
Claims
1. A method, comprising: receiving a dataset associated with a
plurality of photon emission events interacting with a detector
array of an imaging device, wherein the dataset contains at least
one characteristic of each of the plurality of photon emission
events including a spatial position and an energy identified using
single photon emission computed tomography; identifying a first
subset of the dataset associated with a plurality of unscattered
photon emission events from the plurality of photon emission
events; identifying a second subset of the dataset associated with
at least one scattered photon event from the plurality of photon
emission events, wherein the identifying a second subset of the
dataset associated with at least one scattered photon event
comprises estimating a scatter fraction in the photopeak energy
window for each pixel within the received image; determining, for a
scattered photon event, a likely location of emission of the
scattered photon event using data from the first subset of the
dataset associated with the plurality of unscattered photon events
based upon the at least one characteristic; correcting the dataset
by associating the scattered photon event with the determined
likely location of emission; and providing, to a system, an image
generated from the corrected dataset.
2. The method of claim 1, wherein the determining a likely location
of emission comprises calculating a spatial distribution of the
unscattered photon emission events.
3. The method of claim 1, wherein the detector array comprises an
array of pixelated semiconductor detectors selected from the group
consisting of: CdZnTe, CdTe, HgI, Si, and direct-conversion
materials.
4. The method of claim 1, wherein the correcting the dataset
comprises performing iterative image reconstruction with scatter
included using an algorithm selected from the group consisting of:
iterative algebraic, iterative statistical, and iterative learned
reconstruction methods.
5. The method of claim 4, wherein the performing iterative image
reconstruction with scatter included comprises modeling Compton
scattering within at least one projection selected from the group
consisting of: forward projections and back projections of the
iterative image reconstruction algorithm.
6. The method of claim 1, wherein the determining a likely location
of emission comprises accessing a model of an imaged subject.
7. The method of claim 6, wherein the identifying a second subset
of the dataset associated with at least one scattered photon event
comprises using the accessed model to identify projected imaging
locations of scattered photon events.
8. (canceled)
9. (canceled)
10. (canceled)
11. An information handling device, comprising: a processor; a
memory device that stores instructions executable by the processor
to: receive a dataset associated with a plurality of photon
emission events interacting with a detector array of an imaging
device, wherein the dataset contains at least one characteristic of
each of the plurality of photon emission events including a spatial
position and an energy identified using single photon emission
computed tomography; identify a first subset of the dataset
associated with a plurality of unscattered photon emission events
from the plurality of photon emission events; identify a second
subset of the dataset associated with at least one scattered photon
event from the plurality of photon emission events, wherein the
identifying a second subset of the dataset associated with at least
one scattered photon event comprises estimating a scatter fraction
in the photopeak energy window for each pixel within the received
image; determine, for a scattered photon event, a likely location
of emission of the scattered photon event using data from the first
subset of the dataset associated with the plurality of unscattered
photon events based upon the at least one characteristic; correct
the dataset by associating the scattered photon event with the
determined likely location of emission; and provide, to a system,
an image generated from the corrected dataset.
12. The device of claim 11, wherein the determining a likely
location of emission comprises calculating a spatial distribution
of the unscattered photon emission events.
13. The device of claim 11, wherein the detector array comprises an
array of pixelated semiconductor detectors selected from the group
consisting of: CdZnTe, CdTe, HgI, Si, and direct-conversion
materials.
14. The device of claim 11, wherein the correcting the dataset
comprises performing iterative image reconstruction with scatter
included using an algorithm selected from the group consisting of:
iterative algebraic, iterative statistical, and iterative learned
reconstruction methods.
15. The device of claim 14, wherein the performing iterative image
reconstruction with scatter included comprises modeling Compton
scattering within at least one projection selected from the group
consisting of: forward projections and back projections of the
iterative image reconstruction algorithm.
16. The device of claim 11, wherein the determining a likely
location of emission comprises accessing a model of an imaged
subject.
17. The device of claim 16, wherein the identifying a second subset
of the dataset associated with at least one scattered photon event
comprises using the accessed model to identify projected imaging
locations of scattered photon events.
18. (canceled)
19. (canceled)
20. A product, comprising: a storage device that stores code, the
code being executable by a processor and comprising: code that
receives a dataset associated with a plurality of photon emission
events interacting with a detector array of an imaging device,
wherein the dataset contains at least one characteristic of each of
the plurality of photon emission events including a spatial
position and an energy identified using single photon emission
computed tomography; code that identifies a first subset of the
dataset associated with a plurality of unscattered photon emission
events from the plurality of photon emission events; code that
identifies a second subset of the dataset associated with at least
one scattered photon event from the plurality of photon emission
events, wherein the identifying a second subset of the dataset
associated with at least one scattered photon event comprises
estimating a scatter fraction in the photopeak energy window for
each pixel within the received image; code that determines, for a
scattered photon event, a likely location of emission of the
scattered photon event using data from the first subset of the
dataset associated with the plurality of unscattered photon events
based upon the at least one characteristic; code that corrects the
dataset by associating the scattered photon event with the
determined likely location of emission; and code that provides, to
a system, an image generated from the corrected dataset.
Description
BACKGROUND
[0001] Imaging devices perform many different functions such as
medical imaging, security screening, image capture, or the like.
The source of the imaging may be a radiological source, visible
light, non-visible light, or any type of source for which the
imaging device is capable of detection. For example, in a medical
setting, a patient may be injected with a radiopharmaceutical
tracer agent and the imaging device may capture the emission of
gamma photon radiation from the patient's body for diagnostic
analysis. The imaging device may include a gamma camera sensitive
to the emission source, for example, a camera including a specific
substance or object that is sensitive to or reacts to the emission
source. The camera may contain individual pixels which may allow
the imaging source to determine the location, energy, timing, and
intensity of the emitted signal.
BRIEF SUMMARY
[0002] In summary, one aspect provides a method, comprising:
receiving a dataset associated with a plurality of photon emission
events interacting with a detector array of an imaging device;
identifying a first subset of the dataset associated with a
plurality of unscattered photon emission events from the plurality
of photon emission events; identifying a second subset of the
dataset associated with at least one scattered photon event from
the plurality of photon emission events; determining, for a
scattered photon event, a likely location of emission of the
scattered photon event using data from the first subset of the
dataset associated with the plurality of unscattered photon events;
and correcting the dataset by associating the scattered photon
event with the determined likely location of emission.
[0003] Another aspect provides an information handling device,
comprising: a processor; a memory device that stores instructions
executable by the processor to: receive a dataset associated with a
plurality of photon emission events interacting with a detector
array of an imaging device; identify a first subset of the dataset
associated with a plurality of unscattered photon emission events
from the plurality of photon emission events; identify a second
subset of the dataset associated with at least one scattered photon
event from the plurality of photon emission events; determine, for
a scattered photon event, a likely location of emission of the
scattered photon event using data from the first subset of the
dataset associated with the plurality of unscattered photon events;
and correct the dataset by associating the scattered photon event
with the determined likely location of emission.
[0004] A further aspect provides a product, comprising: a storage
device that stores code, the code being executable by a processor
and comprising: code that receives a dataset associated with a
plurality of photon emission events interacting with a detector
array of an imaging device; code that identifies a first subset of
the dataset associated with a plurality of unscattered photon
emission events from the plurality of photon emission events; code
that identifies a second subset of the dataset associated with at
least one scattered photon event from the plurality of photon
emission events; code that determines, for a scattered photon
event, a likely location of emission of the scattered photon event
using data from the first subset of the dataset associated with the
plurality of unscattered photon events; and code that corrects the
dataset by associating the scattered photon event with the
determined likely location of emission.
[0005] The foregoing is a summary and thus may contain
simplifications, generalizations, and omissions of detail;
consequently, those skilled in the art will appreciate that the
summary is illustrative only and is not intended to be in any way
limiting.
[0006] For a better understanding of the embodiments, together with
other and further features and advantages thereof, reference is
made to the following description, taken in conjunction with the
accompanying drawings. The scope of the invention will be pointed
out in the appended claims.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS
[0007] FIG. 1 illustrates an example of information handling device
circuitry.
[0008] FIG. 2 illustrates another example of information handling
device circuitry.
[0009] FIG. 3 illustrates another embodiment of an imaging device
that may use the disclosed embodiments.
[0010] FIG. 4 illustrates a further example of information handling
device circuitry for the example imaging device of FIG. 3 that may
use the disclosed embodiments.
[0011] FIG. 5 illustrates a method of determining a scattered event
within an image.
[0012] FIG. 6 illustrates examples of scatter angle and relative
count density with respect to gamma energy and energy
resolution.
DETAILED DESCRIPTION
[0013] It will be readily understood that the components of the
embodiments, as generally described and illustrated in the figures
herein, may be arranged and designed in a wide variety of different
configurations in addition to the described example embodiments.
Thus, the following more detailed description of the example
embodiments, as represented in the figures, is not intended to
limit the scope of the embodiments, as claimed, but is merely
representative of example embodiments.
[0014] Reference throughout this specification to "one embodiment"
or "an embodiment" (or the like) means that a particular feature,
structure, or characteristic described in connection with the
embodiment is included in at least one embodiment. Thus, the
appearance of the phrases "in one embodiment" or "in an embodiment"
or the like in various places throughout this specification are not
necessarily all referring to the same embodiment.
[0015] Furthermore, the described features, structures, or
characteristics may be combined in any suitable manner in one or
more embodiments. In the following description, numerous specific
details are provided to give a thorough understanding of
embodiments. One skilled in the relevant art will recognize,
however, that the various embodiments can be practiced without one
or more of the specific details, or with other methods, components,
materials, et cetera. In other instances, well known structures,
materials, or operations are not shown or described in detail to
avoid obfuscation.
[0016] Users of imaging devices often desire image output of a high
spatial, temporal, and energy resolution. For example, a medical
image having high spatial, temporal, and energy resolution may
influence a patient's care by directing a physician to a location
of interest within the patient's body. Many imaging devices utilize
a camera sensitive to the type of emission being imaged in order to
accurately capture an image. To capture the image, the camera image
is divided into discrete areas or picture elements (pixels), where
each pixel may represent both a location and an intensity within
the image captured.
[0017] By way of illustration, in a nuclear medicine (molecular
imaging) setting, a patient may be injected with a
radiopharmaceutical tracer agent and the imaging device (gamma
camera) may capture the emission of gamma photon radiation from the
patient's body for diagnostic analysis. The detectors in a gamma
camera may comprise a scintillator with coupled photon detectors
(for example, photomultiplier tubes) or may comprise semiconductor
direct-conversion materials such as CdZnTe, CdTe, HgI, and Si. A
gamma photon detector pixel array comprising a semiconductor
direct-conversion detector material has advantages over
scintillator plus photon detector gamma cameras, including superior
energy and spatial resolution. However, a disadvantage of all gamma
cameras is a loss of signal due to Compton scattering of emission
photons in the body of the patient during imaging. For example, in
a medical imaging application such as SPECT (Single-Photon Emission
Computed Tomography) gamma photons from an emission source within
the body of the patient may be scattered by collision with tissue
and bone between the point of emission and the imaging pixel in the
gamma camera. Since image formation typically may require accepting
counts only within an energy window closely surrounding the
photopeak, scattered counts may be included in the image, producing
a blurring effect. Typically, an estimate is made of the scatter
component of the image, which can be up to 60% of the image counts
in human patients, and scatter is subtracted from the image to
produce a "scatter corrected" image, approximately comprising an
image of only unscattered photon emissions. As will be apparent to
those skilled in the art, a patient must be given a higher dose of
a radioactive tracer because a significant fraction of the photon
emission events detected by the gamma camera will be discarded as
scatter during image reconstruction. This invention provides a
novel solution to the loss of scatter data and allows more
efficient detection using a smaller radiation dose or a shorter
examination time or a combination of the two.
[0018] Currently, many SPECT imaging devices produce an image
preferentially from unscattered photon events in which scattered
photon events may be treated as noise or non-useful data.
Therefore, photon events due to scatter within the patient may be
completely ignored, resulting in a blurring and loss of image
contrast, or discarded, if the scatter component can be estimated.
In some systems, the energy resolution of the imaging device may
not be high enough to cleanly separate unscattered events from
scattered events, resulting in an image comprising both scattered
and unscattered emission photons. What is needed is an efficient
and high-energy-resolution imaging device that can detect scattered
photon events and exploit these scattered events as useful data in
the formation of photon emission images. The solution described
herein may be used in a medical setting to reduce radiological
dosing to patients, reduce imaging time, improve diagnosis, lower
costs, improve patient outcomes, and provide better imaging data to
healthcare professionals.
[0019] Accordingly, an embodiment provides a system and method of
correcting an image by associating at least one scattered photon
event with the location of a plurality of unscattered photon
events. In an embodiment, an imaging device may receive a plurality
of photon emission events including both unscattered and scattered
photon emissions. The imaging system may reconstruct an image of
the source locations in the patient's body that is predominantly
due to the unscattered photon emissions. The imaging device may
also identify at least one scattered photon emission event. In an
embodiment, an image may be corrected by associating the at least
one scattered photon emission event with the source location in the
patient's body most likely associated with the scattered photon
event. In an embodiment, a scattered photon emission event may be
added to the image at or near the most likely source location in
the patient's body. Other methods of associating at least one
scattered photon emission event to the most likely source location
are described and disclosed.
[0020] Such systems and methods provide a technical improvement to
current imaging techniques. Rather than discarding or misreading
scattered photon emission events, the embodiments as described
herein capture useful clinical image information from both
unscattered and scattered photon emission events. The system can
identify a scattered photon emission event by its energy, which
determines a range of Compton scattering angles, thereby providing
a system and method for reconstructing images using the scattered
photon emission events, rather than discarding them as unwanted
image noise. These improvements may be important for medical
imaging, lower patient dosing of imaging reagents, reduce
exam/procedure time, or the like.
[0021] The illustrated example embodiments will be best understood
by reference to the figures. The following description is intended
only by way of example, and simply illustrates certain example
embodiments.
[0022] One embodiment of scattered photon imaging applies to smart
phones, tablets, and the like, that ubiquitously include a
pixelated optical photography camera and display of the pixelated
image. While various other circuits, circuitry or components may be
utilized in information handling devices, with regard to smart
phone and/or tablet circuitry 100, an example illustrated in FIG. 1
includes a system on a chip design found for example in tablet or
other mobile computing platforms. Software and processor(s) are
combined in a single chip 110. Processors comprise internal
arithmetic units, registers, cache memory, busses, I/O ports, etc.,
as is well known in the art. Internal busses and the like depend on
different vendors, but essentially all the peripheral devices (120)
may attach to a single chip 110. The circuitry 100 combines the
processor, memory control, and I/O controller hub all into a single
chip 110. Also, systems 100 of this type do not typically use SATA
or PCI or LPC. Common interfaces, for example, include SDIO and
I2C.
[0023] There are power management chip(s) 130, e.g., a battery
management unit, BMU, which manage power as supplied, for example,
via a rechargeable battery 140, which may be recharged by a
connection to a power source (not shown). In at least one design, a
single chip, such as 110, is used to supply BIOS like functionality
and DRAM memory.
[0024] System 100 typically includes one or more of a WWAN
transceiver 150 and a WLAN transceiver 160 for connecting to
various networks, such as telecommunications networks and wireless
Internet devices, e.g., access points. Additionally, devices 120
are commonly included, e.g., an image sensor such as a camera.
System 100 often includes a touch screen 170 for data input and
display/rendering. System 100 also typically includes various
memory devices, for example flash memory 180 and SDRAM 190. The
components described herein may be adapted for use in an imaging
device.
[0025] FIG. 2 depicts a block diagram of another example of
information handling device circuits, circuitry or components. The
example depicted in FIG. 2 may correspond to computing systems such
as personal computers, laptop computers, or other devices that may
embody imaging scattered photons detected by the pixelated digital
cameras such devices ubiquitously comprise. The scatter imaging may
also be performed on the computing system when it is attached to a
gamma camera, such as in a medical imaging application. As is
apparent from the description herein, embodiments may include other
features or only some of the features of the example illustrated in
FIG. 2.
[0026] The example of FIG. 2 includes a so-called chipset 210 (a
group of integrated circuits, or chips, that work together,
chipsets) with an architecture that may vary depending on
manufacturer (for example, INTEL, AMD, ARM, etc.). INTEL is a
registered trademark of Intel Corporation in the United States and
other countries. AMD is a registered trademark of Advanced Micro
Devices, Inc. in the United States and other countries. ARM is an
unregistered trademark of ARM Holdings plc in the United States and
other countries. The architecture of the chipset 210 includes a
core and memory control group 220 and an I/O controller hub 250
that exchanges information (for example, data, signals, commands,
etc.) via a direct management interface (DMI) 242 or a link
controller 244. In FIG. 2, the DMI 242 is a chip-to-chip interface
(sometimes referred to as being a link between a "northbridge" and
a "southbridge"). The core and memory control group 220 include one
or more processors 222 (for example, single or multi-core) and a
memory controller hub 226 that exchange information via a front
side bus (FSB) 224; noting that components of the group 220 may be
integrated in a chip that supplants the conventional "northbridge"
style architecture. One or more processors 222 comprise internal
arithmetic units, registers, cache memory, busses, I/O ports, etc.,
as is well known in the art.
[0027] In FIG. 2, the memory controller hub 226 interfaces with
memory 240 (for example, to provide support for a type of RAM that
may be referred to as "system memory" or "memory"). The memory
controller hub 226 further includes a low voltage differential
signaling (LVDS) interface 232 for a display device 292 (for
example, a CRT, a flat panel, touch screen, etc.). A block 238
includes some technologies that may be supported via the LVDS
interface 232 (for example, serial digital video, HDMI/DVI, display
port). The memory controller hub 226 also includes a PCI-express
interface (PCI-E) 234 that may support discrete graphics 236.
[0028] In FIG. 2, the I/O hub controller 250 includes a SATA
interface 251 (for example, for HDDs, SDDs, etc., 280), a PCI-E
interface 252 (for example, for wireless connections 282), a USB
interface 253 (for example, for devices 284 such as a digitizer,
keyboard, mice, cameras, phones, microphones, storage, other
connected devices, etc.), a network interface 254 (for example,
LAN), a GPIO interface 255, a LPC interface 270 (for ASICs 271, a
TPM 272, a super I/O 273, a firmware hub 274, BIOS support 275 as
well as various types of memory 276 such as ROM 277, Flash 278, and
NVRAM 279), a power management interface 261, a clock generator
interface 262, an audio interface 263 (for example, for speakers
294), a TCO interface 264, a system management bus interface 265,
and SPI Flash 266, which can include BIOS 268 and boot code 290.
The I/O hub controller 250 may include gigabit Ethernet
support.
[0029] The system, upon power on, may be configured to execute boot
code 290 for the BIOS 268, as stored within the SPI Flash 266, and
thereafter processes data under the control of one or more
operating systems and application software (for example, stored in
system memory 240). An operating system may be stored in any of a
variety of locations and accessed, for example, according to
instructions of the BIOS 268. As described herein, a device may
include fewer or more features than shown in the system of FIG.
2.
[0030] Information handling device circuitry, as for example
outlined in FIG. 1 or FIG. 2, may be used in devices such as
tablets, smart phones, personal computer devices generally, and/or
electronic devices which users may use in or with systems as
described herein. For example, the circuitry outlined in FIG. 1 may
be implemented in a tablet or smart phone embodiment, whereas the
circuitry outlined in FIG. 2 may be implemented in a personal
computer embodiment.
[0031] Referring to FIG. 3, the pixelated detectors and/or gamma
cameras of the various embodiments may be provided as part of
different types of imaging systems, for example, nuclear medicine
(NM) imaging systems such as positron emission tomography (PET)
imaging systems, single-photon emission computed tomography (SPECT)
imaging systems and/or x-ray imaging systems and x-ray computed
tomography (CT) imaging systems, among others. For example, FIG. 3
is a perspective view of an exemplary embodiment of a medical
imaging system 310 constructed in accordance with various
embodiments, which in this exemplary embodiment is a SPECT imaging
system. The system 310 includes an integrated gantry 312 that
further includes a rotor 314 oriented about a gantry central bore
332. The rotor 314 is configured to support one or more NM
pixelated cameras 318 and associated collimators 317 (two cameras
318 and two collimator 317 are shown), such as, but not limited to
gamma cameras, SPECT detectors, multi-layer pixelated cameras
(e.g., Compton camera) and/or PET detectors. It should be noted
that when the medical imaging system 310 includes a CT camera or an
x-ray camera, the medical imaging system 310 also includes an x-ray
tube (not shown) for emitting x-ray radiation towards the
detectors. In various embodiments, the cameras 318 are formed from
pixelated detectors as described in more detail herein. The rotors
314 are further configured to rotate axially about an examination
axis 319.
[0032] A patient table 320 may include a bed 322 slidingly coupled
to a bed support system 324, which may be coupled directly to a
floor or may be coupled to the gantry 312 through a base 326
coupled to the gantry 312. The bed 322 may include a stretcher 328
slidingly coupled to an upper surface 330 of the bed 322. The
patient table 320 is configured to facilitate ingress and egress of
a patient (not shown) into an examination position that is
substantially aligned with examination axis 319 and in which the
patient is located in the field of view of the gamma cameras 318.
During an imaging scan, the patient table 320 may be controlled to
move the bed 322 and/or stretcher 328 axially into and out of a
bore 332. The operation and control of the imaging system 310 may
be performed in any manner known in the art. It should be noted
that the various embodiments may be implemented in connection with
imaging systems that include rotating gantries or stationary
gantries.
[0033] Referring now to FIG. 4 which illustrates a block diagram
illustrating an imaging system 450 that has a plurality of
pixelated imaging detectors and/or gamma cameras configured in
accordance with various embodiments mounted on a gantry. It should
be noted that the imaging system may also be a multi-modality
imaging system, such as an NM/CT imaging system. The imaging system
450, illustrated as a SPECT imaging system, generally includes a
plurality of pixelated imaging detectors 452 and 454 (two are
illustrated) mounted on a gantry 456. It should be noted that
additional imaging detectors may be provided. The imaging detectors
452 and 454 are located at multiple positions (e.g., in an "L-mode"
90 degree configuration, as shown) with respect to a patient 458 in
a bore 460 of the gantry 456. The patient 458 is supported on a
patient table 462 such that radiation or imaging data specific to a
structure of interest (e.g., the heart) within the patient 458 may
be acquired. It should be noted that although the imaging detectors
452 and 454 are configured for movable operation (azimuthally
around, radially in or out, rotatably around an axis, tiltably
about a pivot, and the like) of the gantry 456, in some imaging
systems, imaging detectors are fixedly coupled to the gantry 456
and in a stationary position, for example, in a PET imaging system
(e.g., a ring of imaging detectors). It also should be noted that
the imaging detectors 452 and 454 may be formed from different
materials as described herein and provided in different
configurations known in the art, such as flat or curved panels.
[0034] One or more collimators may be provided in front of the
radiation detection face (317 in FIG. 3, but not shown in FIG. 4)
of one or more of the imaging detectors 452 and 454. The imaging
detectors 452 and 454 acquire a 2D image that may be defined by the
x and y location of a pixel and the location of the imaging
detectors 452 and 454. The radiation detection face (not shown) is
directed towards, for example, the patient 458, which may be a
human patient, animal, airport baggage, or the like.
[0035] A controller unit 464 may control the movement and
positioning of the patient table 462 with respect to the imaging
detectors 452 and 454 and the movement and positioning of the
imaging detectors 452 and 454 with respect to the patient 458 to
position the desired anatomy of the patient 458 within the fields
of view (FOVs) of the imaging detectors 452 and 454, which may be
performed prior to acquiring an image of the anatomy of interest.
The controller unit 464 may have a table controller 465 and a
gantry motor controller 467 that each may be automatically
commanded by a processing unit 468, manually controlled by an
operator, or a combination thereof. The table controller 465 may
move the patient table 462 to position the patient 458 relative to
the FOVs of the imaging detectors 452 and 454. Additionally, or
optionally, the imaging detectors 452 and 454 may be moved,
positioned or oriented relative to the patient 458 or rotated about
the patient 458 under the control of the gantry motor controller
467.
[0036] The imaging data may be combined and reconstructed into an
image, which may comprise 2D images, a 3D volume or a 3D volume
over time (4D).
[0037] A Data Acquisition System (DAS) 470 receives analog and/or
digital electrical signal data produced by the imaging detectors
452 and 454 and decodes the data for subsequent processing as
described in more detail herein. An image reconstruction processor
472 receives the data from the DAS 470 and reconstructs an image
using any reconstruction process known in the art. A data storage
device 474 may be provided to store data from the DAS 470 or
reconstructed image data. An input device 476, such as a keyboard,
mouse, touchscreen, or the like also may be provided to receive
user inputs and a display 478 may be provided to display
reconstructed images. A charge location determination module 480
may provide x and y position for each gamma photon interaction with
the pixelated imaging detectors 452 and 454. In an embodiment, a
depth-of-interaction z position may be determined.
[0038] In an embodiment, the imaging device may be installed in a
location for security scanning. For example, the device may be in
an airport security checkpoint, a baggage screening location, or
the like. The device may comprise a plurality of x-ray sources and
a plurality of pixelated photon detector arrays. In an embodiment,
the imaging device may be permanently anchored, moveable, or
completely portable. For example, an imaging device may be a
hand-held device for use by first responders, security, or
assessment teams. Other uses outside of a security setting are
contemplated and are disclosed. As should be understood by one
skilled in the art, both healthcare imaging and security screening
are merely examples. Other possible applications for the techniques
as described herein are possible and contemplated.
[0039] In an embodiment, the receiving equipment may contain
sensors that are sensitive to radiological particles or photons.
The receiving equipment may record communication events, also
referred to as interactions, on an array of sensors located in the
receiving equipment. Each of the sensors in the array may be
represented as a pixel in the final image. During the course of
imaging, a photon or particle may strike one or more pixel
detection units. In an embodiment, the signals received from the
one or more pixel detection units may be used to separate
unscattered and scattered photon emissions and to reconstruct an
image using both. In a healthcare setting this may allow healthcare
professionals to achieve better imaging in less time and with less
radiolabel dose delivered to a patient which may result in better
treatment plans and decrease medical costs, for example, better
efficiency may be achieved and imaging sessions' durations may be
reduced.
[0040] Referring now to FIG. 5, an embodiment of an imaging device
and method may be in a healthcare setting, security screening,
manufacturing, or any application where an imaging device may be
utilized. For example, the imaging device may be a radiological
imaging device in which radiological matter (consisting of
particles or photons) is either transmitted through or injected
into and emitted from a patient's body. Another example may include
an airport or port of entry device used to scan for radiation or
other material of interest for security purposes. Another example
of an imaging device may be used by first responder to determine
environmental conditions and/or safety of a location. Other uses
are contemplated and disclosed.
[0041] At step 501 an embodiment may acquire one or more projection
images of photon emissions. Acquiring an image may comprise
receiving or capturing a communication event occurring within a
photon detector pixel array. Receiving or capturing an interaction
may include receiving one or more signals from one or more pixel
detection units that indicate an interaction has occurred. For
readability, the discussion herein will refer to a photon as that
object which is causing the interaction and resulting in the
signals. However, it should be understood that the object may
include a photon (light of any spectrum), a radiological particle,
or any type of energy which the detection unit is capable of
detecting. A photon detector pixel array may be one or more pixel
detector units. A photon detector pixel array may be organized in
any configuration such as a grid, a brick pattern, an interspersed
pattern, or the like. The photon detector pixel array may be
oriented in a flat plane, curved plane, or the like. In other
words, the photon detector pixel array may be arranged in a manner
that is suitable for detecting interactions from an emission source
and may be different for different applications. For example, a
photon from an emission source may interact with one or more pixels
on a photon pixel array as part of an imaging unit in a medical
setting. A plurality of projection images is acquired in SPECT
imaging. For example, in a system 310 such as that depicted in FIG.
3, the gantry may rotate 6 degrees between each set of two
projection images (one for each gamma camera 318) until a total of
60 projection images have been acquired. Each of these projection
images may be processed to make corrections for attenuation and/or
scatter before being further processed to reconstruct a 3D image of
the patient's body, particularly showing the distribution of an
injected (or ingested or inhaled) radioisotope tracer.
[0042] In an embodiment a pixel (picture element) refers to a
discrete location on the imaging hardware surface that may be only
a subset of the imaged area. The data or electronic communication
from a pixel or plurality of pixels may be used to form an image as
a composite from the one or more pixels. An imaging device may use
many methods to detect a communication event from a pixel. For
example, in a consumer camera a pixel represents the intensity and
wavelength of the visible light detected by the pixel. As another
example, radiological imaging devices used in cancer screenings,
radiation detectors, and the like, use a type of atomic particle or
photon emitted by a source and measurable by a sensor with
associated circuitry to provide both a location, energy, and
intensity (or count density) of the radiological particles or
photons detected. Using the communication events from the pixels,
an image may be created based upon the location, intensity, and
energy or wavelength of the communication event from the pixel. In
other words, an embodiment may use the signal transmitted from the
pixel during imaging to create an image based upon the information
contained within the signal. The data may be collected from
multiple pixels to create an image of a larger area.
[0043] In an embodiment with a semiconductor detector material, a
photon detector pixel array may have two sides with metallic
electrodes deposited on the semiconductor detector crystal. A first
side may comprise a plurality of pixels, also referred to as the
pixelated side, which may be arranged in a grid pattern. This side
may be coupled to read-out electronics that can capture the signal
from the pixelated side. In the case of CdZnTe (CZT) or CdTe, in
which the electron mobility is much larger than hole mobility, the
pixelated side may be the anode side of the array and provide anode
signals. In some configurations, this side may be connected to
ground potential. In an embodiment, a second side of the detector
pixel array may be substantially opposite the first side, for
example, in the case of a thick sheet-like detector, the first side
may be the bottom side, and the second side may be the top side,
typically the side from which gamma photons may be incident upon
the detector. This second side of the detector pixel array may be a
cathode and may be connected to a negative voltage bias.
[0044] At step 502 an embodiment may estimate the scatter fraction
in the photopeak energy window for each pixel in each projection
image, and then subtract the estimated number of scattered photon
emission events from each pixel. Several possible methods for
estimating scatter fraction are discussed below.
[0045] At step 503 an image of the emission source locations within
a patient's body may be reconstructed from a plurality of
projection images. Because the scatter fraction was estimated and
subtracted at step 502, the resulting reconstructed image is
labelled as "scatter-corrected." This type of image is typically
produced in commercial SPECT systems, often with additional
corrections for attenuation and resolution recovery. In a
solid-state semiconductor photon detector pixel array, the energy
resolution may be very good. For example, in CZT detectors, the
energy resolution may be 3-4% FWHM (full-width at half maximum of
the photopeak) at 140 keV, much better in comparison with a NaI
scintillator detector with energy resolution of about 10% FWHM at
140 keV. The superior energy resolution enables more effective
discrimination between scattered photon emissions and unscattered
photon emissions, because the scattered photons always have lower
energy than the unscattered photons. This will be highlighted in
the discussion below of FIG. 6.
[0046] The predominantly unscattered photon emission events may be
reconstructed into an image of the photon emission source locations
within the patient's body. The SPECT image reconstruction may be
any method known in the art, including filtered back-projection
(FBP), MLEM (Maximum Likelihood Expectation Maximization) or OSEM
(Ordered Subset Expectation Maximization), or ART (Algebraic
Reconstruction Technique), and other iterative algebraic, iterative
statistical, and iterative learned reconstruction methods. The
image may be corrected for the presence of scattered photon
emission events by estimating the scattered component of the image
and subtracting the estimate from the original image. This will be
a more efficient part of the process when semiconductor photon
detector pixel arrays are used with their superior energy
resolution. Far fewer scattered photon events will be mixed with
the unscattered photon events, so it is easier to separate the
scattered events and reconstruct a predominantly unscattered image
of the source locations of unscattered photon emissions.
[0047] For example, FIG. 6 illustrates several graphs of gamma
photon emission events with Compton scatter in the patient's body
before detection by a gamma camera. The graphs are computed using
the well-known Compton scattering formula:
E SC = E 0 1 + ( E 0 / m e c 2 ) ( 1 - cos .theta. ) ,
##EQU00001##
where E.sub.0 is the energy of the gamma photon emission, typically
140 keV for .sup.99mTc, a common isotope for medical imaging,
E.sub.sc is the energy of the scattered gamma photon,
m.sub.ec.sup.2 is the rest energy of an electron, 511 keV, from
which the emitted gamma photon scatters, and .theta. is the
scattering angle. The top two graphs 601 and 602 illustrate the
effect of Compton scatter on a typical NaI scintillator gamma
camera where the energy resolution may be about 10% FWHM (14 keV
for the 140 keV photopeak). The bottom two graphs 603 and 604
illustrate the effect of Compton scatter on a CZT pixelated gamma
camera where the energy resolution may be about 3% FWHM (4 keV for
the 140 keV photopeak). In SPECT imaging, detected photon events
within an energy window centered on the photopeak with width of
about .+-.FWHM are included in the image. In the top two graphs 601
and 602, the imaging energy window consists of all detected photon
events between the two vertical dashed lines at 140-14=126 keV and
140+14=154 keV. Similarly, for the bottom two graphs 603 and 604,
the energy window consists of all detected photon events between
the two vertical dashed lines at 140-4=136 keV and 140+4=144
keV.
[0048] In FIG. 6, the two graphs on the right 602 and 604
illustrate the energy spectra (relative count density as a function
of gamma photon energy) for both unscattered photons (solid
Gaussian shaped peaks) and the singly-scattered photons (heavy
dashed curves). The shape of the scattered photon spectra was
calculated using the well-known Klein-Nishina formula, convolved
with the Gaussian with either 10% FWHM (for 602) or 3% FWHM (for
604). Of course, the scattered photons can scatter multiple times
before exiting the patient's body and interacting with the photon
detector array, but the key aspect of the invention is apparent by
considering only a single scatter event. The light gray-shaded
areas 611, 612, 613, and 614 represent the scattered photons that
are detected within the energy windows that may be used for image
formation. As noted in the title of the graph 602, when the energy
resolution is about 10% (scintillator gamma cameras), the fraction
of events from a single Compton scatter within the patient can be
about 40% of the total detected spectrum (dotted line peak) in this
illustrative calculation. The title of graph 604 similarly
discloses that when the energy resolution is about 3% (CZT gamma
cameras), the fraction of events from a single Compton scatter
within the patient can be about 5% of the total detected spectrum
(dotted line peak) in this illustrative calculation. Clearly the
superior energy resolution of a CZT gamma camera benefits SPECT
imaging by including substantially less scattered photons in the
photopeak image. This benefit of superior energy resolution can be
used to enable the invention we describe herein.
[0049] In FIG. 6, the two graphs on the left 601 and 603 illustrate
the Compton scattering angle in degrees as a function of the energy
of the scattered gamma photon. The gray-shaded region 611 in graph
601 includes scatter in the imaging window at scatter angle up to
almost 90 degrees due in part to a scatter window of about .+-.10%
(scintillator gamma cameras) of the photopeak energy of 140 keV.
Therefore, scatter events may be included in the energy window
resulting in a reconstructed image which may be blurry and have
reduced contrast because of the scattered photon emission events
mixed in with the unscattered photon emission events. Previous
methods may attempt to simply subtract scattered photon emission
events from an image. The gray-shaded region 613 in graph 603
includes scatter in the imaging window at scatter angle below 40
degrees due in part to a scatter window of about .+-.3% (CZT gamma
cameras) of the photopeak energy of 140 keV.
[0050] Now consider in graphs 602 and 604 that there are scattered
photon emission events at energies below the lower bound of the
photopeak energy window. Those scattered photons may be used to
estimate the scatter fraction within the photopeak energy window,
in order to subtract those counts, on a pixel-by-pixel basis. There
may be other methods, such as Monte Carlo simulations based on the
attenuation map derived from an x-ray CT (Computerized Tomography)
or MRI (Magnetic Resonance Imaging) scan of the patient, or
ray-tracing modeling, such as GEANT, that estimate the scattered
photon contribution to the image at each pixel so that it can be
subtracted and thrown away. The superior energy resolution of a
gamma camera employing semiconductor (such as CZT) pixelated photon
detector arrays enables a new option that is superior to all the
methods that throw away scattered photons. Consider graphs 601 and
603 in the energy region below the lower bound of the photopeak
energy window. In graph 601 for 10% energy resolution (scintillator
gamma camera) a scattered photon detected at an energy of 110 keV
will be associated with a range of scattering angles from about 60
to 130 degrees, an uncertainty of about 70 degrees. In contrast, in
graph 603 for 3% energy resolution (CZT gamma camera) a scattered
photon detected at an energy of 110 keV will be associated with a
range of scattering angles from about 80 to 100 degrees, an
significantly reduced uncertainty of only about 20 degrees. Thus,
better energy resolution, as available with CZT gamma cameras,
results in a much better estimate of the scattering angle, which in
turn results in the ability to predict the location within the
patient's body where the scattered photon emission originated.
[0051] Returning now to FIG. 5, at step 504 an embodiment may use
the full energy spectra projection images to reconstruct a
"scatter-included" 3D image. This is the step that differentiates
this invention from any of the commercial SPECT systems that only
produce "scatter-corrected" (that is, subtracted) images. It is
important that the projection images comprise a full energy
spectrum for each pixel, as this spectral information is required
for using the scattered photons to enhance the reconstructed image.
Notice that an arrow now connects the original uncorrected
projection image data at 501 to the scatter-included reconstruction
at 504. The scatter corrected image produced at 503 is based upon a
photopeak energy window with the estimated scatter fraction in that
window subtracted. This new scatter-included image uses the
scatter-corrected image 503 as an input to the iterative image
reconstruction process, but also uses the original uncorrected
projection images at 501 to build a 3D image of the distribution of
photon emission sources within the patient's body. This requires
that the image reconstruction algorithm models the physical process
of Compton scattering, as well as other physical processes, such as
attenuation and collimator-detector response.
[0052] It would be simpler to identify the scattered photon
emission events if we could assume that all unscattered photon
emission events were confined to the photopeak energy window. This
is not the case for a pixelated photon detector array comprising
CZT direct conversion detectors. There is a fraction of the photon
emission events that interact with the CZT detectors that will
result in charge collection on more than one pixel. This may occur,
for example, because the electron charge cloud is near the edge of
a pixel and the charge collection is shared between two or more
pixels. Two or more pixels may record an interaction because an
initial Compton scatter occurs in one pixel and the final
photoelectric interaction occurs in a different pixel. There may be
a depth-of-interaction dependent collection of charge, due to a
limited lifetime and mobility of either the electron or hole
charges. These and other physical mechanisms may lead to a low
energy spectral tail in a CZT detector. The effect is that some of
the unscattered photon events which belong in the photopeak energy
window may be recorded at lower energies where scattered photon
emission events are expected. It is possible to identify charge
sharing and depth-of-interaction dependent events and to correct
their apparent energy to place them into the photopeak energy
window, where they belong. If such corrections are performed, then
the remaining events at energies below the lower bound of the
photopeak energy window should be predominantly photon emissions
that scattered in the patient's body. At photon emission energies
higher than typical clinical SPECT radioisotopes, a significant
number of the high energy gamma photons will Compton scatter in the
CZT detector and then the scattered photon will escape from the
detector without depositing its remaining energy, leading to a
Compton plateau in the energy spectrum, representing photon
emission events that may or may not have been scattered in the
patient's body. However, this is a small effect at the energies of
typical clinical SPECT radioisotopes.
[0053] At step 505, the method or system may correct an image by
associating one or more scattered photon emission events with the
location in the patient of the source of one or more unscattered
photon emission events. In other words, an embodiment may identify
scattered photon emission events and add the scattered events to a
location in the image that is the most likely location in the
patient for the photon emission before it was scattered. Scattered
photon emission events may be counted as full events, equal in
information content to unscattered events. Alternatively, a
compensation may be made for scattered events to give them a value
less than unscattered events in the image reconstruction.
[0054] The various embodiments described herein thus represent a
technical improvement to imaging devices that may require high
sensitivity and resolution to the material imaged. An embodiment
allows for the association of scattered photon emission events with
the source locations in the patient's body of unscattered photon
emission events. Using the techniques described herein, the
detection efficiency of the system can be substantially improved,
so that rather than requiring longer imaging sessions and/or higher
radiological doses, a more complete image may be achieved with
lower imaging session durations and/or lower radiological doses. By
more effectively removing the scatter background and assigning it
to the appropriate source distribution for photon emissions, the
image contrast and spatial resolution can be substantially
improved. Such a system results in more accurate imaging, less
device down-time, and lower costs associated with the imaging
procedure. Image quantitation may also be improved by using
scattered photons as well as unscattered photons, thus resulting in
more accurate SUV (Standardized Uptake Value) estimation in
SPECT.
[0055] The medical modality of SPECT has been used in this
description of the invention for illustration. As will be
appreciated by one skilled in the art, other medical, security, or
non-destructive testing applications may also benefit from this
invention. SPECT and PET are photon emission modalities; in
contrast, photon transmission modalities such as x-ray CT, x-ray
fluorescence, x-ray mammography, and x-ray radiography may use the
method described to improve performance, including at least one of
detection efficiency, image contrast, spatial resolution, and image
quantitation.
[0056] As will be appreciated by one skilled in the art, various
aspects may be embodied as a system, method or product device.
Accordingly, aspects may take the form of an entirely hardware
embodiment or an embodiment including software that may all
generally be referred to herein as a "circuit," "module" or
"system." Furthermore, aspects may take the form of a product
device embodied in one or more device readable medium(s) having
device readable program code embodied therewith.
[0057] It should be noted that the various functions described
herein may be implemented using instructions stored on a readable
storage medium device such as a non-signal storage device that are
executed by a processor. A storage device may be, for example, an
electronic, magnetic, optical, electromagnetic, infrared, or
semiconductor system, apparatus, or device, or any suitable
combination of the foregoing. More specific examples of a storage
medium would include the following: a portable computer diskette, a
hard disk, a random-access memory (RAM), a read-only memory (ROM),
an erasable programmable read-only memory (EPROM or Flash memory),
a portable compact disc read-only memory (CD-ROM), an optical
storage device, a magnetic storage device, or any suitable
combination of the foregoing. In the context of this document, a
storage device is not a signal and "non-transitory" includes all
media except signal media.
[0058] Program code embodied on a storage medium may be transmitted
using any appropriate medium, including but not limited to
wireless, wireline, optical fiber cable, RF, et cetera, or any
suitable combination of the foregoing.
[0059] Program code for carrying out operations may be written in
any combination of one or more programming languages. The program
code may execute entirely on a single device, partly on a single
device, as a stand-alone software package, partly on single device
and partly on another device, or entirely on the other device. In
some cases, the devices may be connected through any type of
connection or network, including a local area network (LAN) or a
wide area network (WAN), or the connection may be made through
other devices (for example, through the Internet using an Internet
Service Provider), through wireless connections, e.g., near-field
communication, or through a hard wire connection, such as over a
USB connection.
[0060] Example embodiments are described herein with reference to
the figures, which illustrate example methods, devices and program
products according to various example embodiments. It will be
understood that the actions and functionality may be implemented at
least in part by program instructions. These program instructions
may be provided to a processor of a device, a special purpose
information handling device, or other programmable data processing
device to produce a machine, such that the instructions, which
execute via a processor of the device implement the functions/acts
specified.
[0061] It is worth noting that while specific blocks are used in
the figures, and a particular ordering of blocks has been
illustrated, these are non-limiting examples. In certain contexts,
two or more blocks may be combined, a block may be split into two
or more blocks, or certain blocks may be re-ordered or re-organized
as appropriate, as the explicit illustrated examples are used only
for descriptive purposes and are not to be construed as
limiting.
[0062] As used herein, the singular "a" and "an" may be construed
as including the plural "one or more" unless clearly indicated
otherwise.
[0063] This disclosure has been presented for purposes of
illustration and description but is not intended to be exhaustive
or limiting. Many modifications and variations will be apparent to
those of ordinary skill in the art. The example embodiments were
chosen and described in order to explain principles and practical
application, and to enable others of ordinary skill in the art to
understand the disclosure for various embodiments with various
modifications as are suited to the particular use contemplated.
[0064] Thus, although illustrative example embodiments have been
described herein with reference to the accompanying figures, it is
to be understood that this description is not limiting and that
various other changes and modifications may be affected therein by
one skilled in the art without departing from the scope or spirit
of the disclosure.
* * * * *