U.S. patent application number 09/761250 was filed with the patent office on 2001-11-22 for method of and device for forming x-ray images.
Invention is credited to Grass, Michael, Kemkers, Geerd Richard.
Application Number | 20010043671 09/761250 |
Document ID | / |
Family ID | 7627756 |
Filed Date | 2001-11-22 |
United States Patent
Application |
20010043671 |
Kind Code |
A1 |
Grass, Michael ; et
al. |
November 22, 2001 |
Method of and device for forming X-ray images
Abstract
The invention relates to a method of forming X-ray images (B)
from at least two series of projection data sets (P.sub.1, P.sub.2)
successively acquired along different trajectories (T.sub.1,
T.sub.2), a respective 3D data set (S.sub.1, S.sub.2) being formed
from each series of projection data sets (P.sub.1, P.sub.2). In
order to neutralize motions of the patient between the acquisition
of the individual series of projection data sets upon combination
of the 3D data sets so as to form X-ray images which are as free
from artefacts as possible, the invention proposes to determine a
transformation rule (F) describing the location in space of the 3D
data sets (S.sub.1, S.sub.2) relative to one another in such a
manner that voxels are selected in a 3D data set (S.sub.1) and
their location in the other 3D data set (S.sub.2) is determined by
means of a suitable similarity measure, after which X-ray images
(B) are formed from the 3D data sets (S.sub.1, S.sub.2) combined by
means of the transformation rule (F). Consequently, it is possible
to dispense with phantom members that are to be reproduced for fine
adjustment of the individual 3D data sets as well as with manual
fine adjustment steps. The invention also relates to an X-ray
device constructed for this purpose.
Inventors: |
Grass, Michael; (Hamburg,
DE) ; Kemkers, Geerd Richard; (Fairfield,
CT) |
Correspondence
Address: |
Michael E. Marion
Philips Electronics North America Corporation
580 White Plains Road
Tarrytown
NY
10591
US
|
Family ID: |
7627756 |
Appl. No.: |
09/761250 |
Filed: |
January 16, 2001 |
Current U.S.
Class: |
378/210 ;
378/4 |
Current CPC
Class: |
A61B 6/027 20130101;
G06T 3/4053 20130101; G06T 2207/30004 20130101; G06T 7/32
20170101 |
Class at
Publication: |
378/210 ;
378/4 |
International
Class: |
G01N 023/00 |
Foreign Application Data
Date |
Code |
Application Number |
Jan 18, 2000 |
DE |
10001709.6 |
Claims
1. A method of forming X-ray images (B) from at least two series of
projection data sets (P.sub.1, P.sub.2) successively acquired along
different trajectories (T.sub.1, T.sub.2), a respective 3D data set
(S.sub.1, S.sub.2) being formed from each series of projection data
sets (P.sub.1, P.sub.2) and a transformation rule (F), describing
the location in space of the 3D data sets (S.sub.1, S.sub.2)
relative to one another, being determined in that voxels in one 3D
data set (S.sub.1) are selected and their location in the other 3D
data set (S.sub.2) is determined by means of a suitable similarity
measure, and X-ray images (B) being formed from the 3D data sets
(S.sub.1, S.sub.2) combined by way of the transformation rule
(F).
2. A method as claimed in claim 1, characterized in that a
plurality of voxels is selected in each time a sub-volume of a 3D
data set (S.sub.1, S.sub.2) in order to determine the
transformation rule (F).
3. A method as claimed in claim 1, characterized in that individual
sub-volumes (V.sub.1, V.sub.2) containing significant image
information are selected in order to determine the transformation
rule (F).
4. A method as claimed in claim 1, characterized in that the mean
absolute difference, the mean square difference, the double
correlation or the Pearson linear correlation is used as the
similarity measure.
5. A method as claimed in claim 1, characterized in that the
projection data sets (P.sub.1, P.sub.2) are acquired by means of a
C-arm X-ray device (1) or a computed tomography device (17).
6. An X-ray device, notably for carrying out the method claimed in
claim 1, which includes an X-ray source (2) and an X-ray detector
(3) for the acquisition of a plurality of series of projection data
sets (P.sub.1, P.sub.2) along different trajectories (T.sub.1,
T.sub.2) around an object (13) to be examined, a reconstruction
unit (9) for forming 3D data sets (S.sub.1, S.sub.2) from
respective series of projection data sets (P.sub.1, P.sub.2), and
also an arithmetic unit (10) which is constructed in such a manner
that a transformation rule (F) describing the location in space of
the 3D data sets (S.sub.1, S.sub.2) relative to one another is
determined by selecting voxels in a 3D data set (S.sub.1) and by
determining their location in the other 3D data set (S.sub.2) by
means of a suitable similarity measure, X-ray images (B) being
formed from the 3D data sets (S.sub.1, S.sub.2) combined by way of
the transformation rule (F).
7. An X-ray device as claimed in claim 6, characterized in that the
X-ray device is a C-arm X-ray device (1) or a computed tomography
device (17).
Description
[0001] The invention relates to a method of forming X-ray images
from at least two series of projection data sets successively
acquired along different trajectories, a respective 3D data set
being formed from each series of projection data sets. The
invention also relates to an X-ray device which is particularly
suitable for carrying out this method.
[0002] A method and a device of this kind are known from EP 860 696
A2. Therein, two series of projection data sets are acquired along
two semi-circular trajectories by means of a C-arm X-ray device,
said trajectories extending at an angle of 60.degree. relative to
one another. Each series of projection data sets forms a respective
3D data set wherefrom a respective reconstruction image can be
formed. Because a single 3D data set does not contain adequate data
for a complete and correct reconstruction and artefacts occur
during the reconstruction, the two (or more) 3D data sets are
combined by weighted addition. The desired images are formed from
the resultant data set by reconstruction; artefacts occur to a
lesser extent in said images.
[0003] The acquisition of the series of projection data sets along
the different trajectories normally takes place successively in
time. For optimum compatibility of the projection data sets, or the
3D data sets to be formed therefrom, during the subsequent
combination and reconstruction, it would be necessary for the
object to be examined, for example a patient, to remain motionless
during the data acquisition. In particular the position of the
object to be examined should always be identical during the
acquisition of the individual series of projection data sets and
any translatory or rotary motions of the object to be examined
should be as small as possible. However, because this can hardly be
completely achieved during a practical examination of a patient, it
is also known to reproduce, for example a phantom member in the
X-ray images during the acquisition of the projection data sets;
such a phantom can subsequently be used for fine adjustment so as
to achieve matching 3D data sets. This operation is performed by a
user.
[0004] Therefore, it is an object of the invention to provide a
method which enables combination of 3D data sets without it being
necessary for a user to perform a fine adjustment operation. It is
also an object to provide an X-ray device which is suitably
constructed for this purpose.
[0005] These objects are achieved by means of a method as disclosed
in claim 1 and by means of an X-ray device as disclosed in claim
6.
[0006] The invention is based on the recognition of the fact that
the same object to be examined is reproduced in all 3D data sets
and that, therefore, individual structures can be traced in all 3D
data sets. According to the invention this fact is used so as to
select the voxel image values of at least one sub-volume in a first
3D data set and to search for these values in the other 3D data
sets in order to derive therefrom a transformation rule describing
a translatory or rotary motion, if any, occurring between the
formation of individual 3D data sets. Generally speaking, the
sub-volume V.sub.2 is then selected automatically. The search in
the other 3D data sets for voxels selected in a first 3D data set
utilizes a suitable similarity measure for iteratively finding the
corresponding voxel in the other 3D data sets.
[0007] Depending on the desired accuracy, this method can be
performed with the appropriate number of voxels which should be
distributed as well as possible throughout the entire volume
represented by the 3D data set. The transformation rule or
transformation rules found are then used to correct for motions of
the object to be examined, to achieve quasi matching of the 3D data
sets, to combine them so as to form a complete data set and to form
the desired images therefrom. According to the method of the
invention the foregoing can be realized without utilizing a phantom
object or other markers reproduced in the X-ray images; the method
can be performed automatically, that is, without interventions by a
user.
[0008] In order to determine the transformation rule, several
voxels located in respective sub-volumes of a 3D data set and/or
individual voxels containing significant image information are
advantageously selected in conformity with the claims 2 and 3.
[0009] Preferably, the functions indicated in claim 4 are used as a
similarity measure. However, other possibilities are also
feasible.
[0010] The method according to the invention is used primarily for
a C-arm X-ray device, but can also be used in a computed tomography
device; the invention can also be used notably in an X-ray device
or a computed tomography device involving a conical X-ray beam.
[0011] claim 6 discloses an X-ray device according to the invention
which includes an X-ray source, an X-ray detector, a reconstruction
unit and an arithmetic unit.
[0012] The invention will be described in detail hereinafter with
reference to the drawings. Therein:
[0013] FIG. 1 shows a C-arm X-ray device according to the
invention,
[0014] FIG. 2 illustrates two trajectories,
[0015] FIG. 3 shows a block diagram illustrating the method
according to the invention, and
[0016] FIG. 4 shows a computed tomography device constructed in
accordance with the invention.
[0017] The C-arm X-ray device 1 shown in FIG. 1 includes an X-ray
tube 2 which is mounted at one end of the C-arm 20 and an X-ray
detector 3 which is mounted at the other end of the C-arm 20. The
X-ray tube 2 produces a conical X-ray beam 14 which irradiates an
object 13 to be examined, for example, a patient who is arranged on
a patient table 4 in the examination zone, after which the beam is
incident on the two-dimensional X-ray detector 3. The X-ray tube 2
and the X-ray detector 3 are rotatable about the y axis by way of
rails 7 provided on the C-arm 20. Because of the suspension by
means of a plurality of arms and links 5, 6, the position of the
C-arm 20 can be changed in different directions; for example, the
C-arm 20 is capable of rotation about the x, the y and the z
axis.
[0018] Such motions for the acquisition of projections from
different X-ray positions and the data acquisition are controlled
by means of a control unit 8. The projections acquired are applied
to a reconstruction unit 9 which forms a respective 3D data set,
and possibly therefrom a reconstruction image, from a series of
projections acquired along a trajectory. Such 3D data sets, or the
reconstruction images, are subsequently applied to an arithmetic
unit 10 which determines the transformation rules (or the
transformation parameters for a transformation) between the
individual 3D data sets in conformity with the method of the
invention and ultimately forms the desired X-ray images from the 3D
data sets by means of the transformation rules; the desired X-ray
images can be displayed on a monitor 11.
[0019] FIG. 2 shows a sketch illustrating two trajectories T.sub.1
and T.sub.2. Each trajectory describes the path traveled by the
center of the detector surface of the X-ray detector 3 during the
acquisition of projection data sets. The trajectory is, therefore,
the curve extending through all X-ray positions in which a
respective projection is acquired. In the case shown the
trajectories T.sub.1 and T.sub.2 describe a respective semi-circle
and are tilted through an angle of 2.alpha.=90.degree. relative to
one another. A first 3D data set is acquired from the projections
acquired along the trajectory T.sub.1 whereas a second 3D data set
is formed from the projections acquired along the trajectory
T.sub.2. In order to match these data sets, that is, in order to
eliminate any translatory or rotary motion of the patient occurring
between the acquisition of the first and the second series of
projections, the transformation rule between the two 3D data sets
is subsequently determined as will be described in detail
hereinafter with reference to FIG. 3.
[0020] In the block diagram shown in FIG. 3 two sets of projections
P.sub.1(.alpha..sub.1) and P.sub.2(.alpha..sub.2) are symbolically
shown as starting points in the blocks 201 and 202; these two sets
have been acquired along two trajectories T.sub.1 and T.sub.2
extending at angles .alpha..sub.1 and .alpha..sub.2, respectively,
relative to a reference plane. In the blocks 211 and 212 a
respective 3D data set S.sub.1, S.sub.2 is formed from each of the
projection data sets P.sub.1, P.sub.2.
[0021] Subsequently, in the block 22 a transformation rule is
determined from the two 3D data sets S.sub.1, S.sub.2 and is
applied to one (or both) of the two data sets (for example to
S.sub.1).
[0022] The transformation rule is derived, for example, as
follows:
[0023] a) The voxels (for example, 16.times.16.times.16) of a
sub-volume V.sub.1 (that is, a part of the volume
[0024] reproduced by the 3D data set) are selected from one of the
two 3D data sets, for example the data set S.sub.1. This selection
can be performed automatically, for example, by selecting a
sub-volume having an as high as possible contrast (where the voxel
image values in the sub-volume deviate as much as possible from
their mean value).
[0025] b) Subsequently, the co-ordinates x.sub.1 of the voxels in
the sub-volume V.sub.1 are subjected to a transformation, for
example in conformity with the relation:
X.sub.2=(X.sub.1-U)+.dagger. (1)
[0026] where x.sub.1, x.sub.2, u, t are vectors and is a rotation
matrix which describes in the transformation of the co-ordinates
upon a rotation of the co-ordinate system about its origin. Only
the vector x.sub.1 from among the vectors is known (this is the
vector which connects the voxel to the co-ordinate origin). The
vector u represents the co-ordinates of the point around which the
rotation takes place and t is a vector corresponding to the
translation of the voxel. The resultant vector x.sub.2 represents
the co-ordinates of the voxel in the volume represented by the
second 3D data set. When the transformation is applied to all
voxels of the sub-volume, an equally large sub-volume V.sub.2 will
be obtained in the second data set S.sub.2.
[0027] c) Subsequently, the correspondence between the voxel image
values of the sub-volume V.sub.2 and the voxel image values of the
sub-volume V.sub.1 of the first 3D data set S.sub.1 is evaluated by
way of a similarity measure. Subsequently, the position and/or the
orientation of the sub-volume selected in the second data set is
varied (by varying u, t, or ) and the similarity between this
sub-volume and the sub-volume V.sub.1 is again evaluated by way of
the similarity measure. These steps are iteratively repeated until
the sub-volume which exhibits the best correspondence to the
sub-volume V.sub.1 of the 3D data set S.sub.1 is found from the 3D
data set S.sub.2. The associated transformation parameters (u, t,
or ) then define the transformation rule.
[0028] For example, the mean absolute difference MAD of the voxel
image values in the two volumes can be taken as the similarity
measure: 1 MAD = 1 n i = 1 n ( V 1 i - V 2 i )
[0029] where n is the number of voxels in the sub-volume V.sub.1 or
V.sub.2, and V.sub.1i and V.sub.2i are the i.sup.th voxel image
value in the first sub-volume V.sub.1 and in the second sub-volume
V.sub.2, respectively. Instead of minimizing the mean absolute
difference, for example, the root of the square differences can
also be minimized or the similarity can be evaluated by means of a
suitable correlation coefficient (for example, for a
cross-correlation, double correlation or the Pearson linear
correlation).
[0030] The extraction of the transformation parameters from a
sub-volume requires less calculation time than if these parameters
were determined while utilizing all voxel image values of the 3D
data sets. However, it is less accurate and more influenced by
noise. The accuracy can be improved by taking into account two or
more sub-volumes for each 3D data set and by averaging the
transformation parameters found for the various sub-volumes.
[0031] The described transformation is based on the assumption that
a rigid object to be examined is present in the examination zone.
The object, however, could also be deformable. The
location-dependent transformation parameters could then be
determined by means of a so-called "elastic matching" method.
[0032] In the block 23 an improved 3D data set S is determined from
the transformed 3D data set S.sub.1 and from S.sub.2 by way of
preferably weighted summing of the voxel image values of voxels
which correspond to one another in conformity with the
transformation. As the weighting factor whereby a voxel image value
is multiplied is greater, its distance from the plane defined by
the associated trajectory T.sub.1 or T.sub.2 will be smaller (and
vice versa) and the less the noise and the artefacts will be. This
is because the artefacts in the two 3D data sets S.sub.1 and
S.sub.2 become more manifest in the voxels which are situated
comparatively far from said plane.
[0033] FIG. 4 shows a computed tomography device according to the
invention. The X-ray source 2' with a collimator 19 for producing a
conical X-ray beam 15 and the X-ray detector 3' are mounted on a
ring-shaped gantry 18; for the acquisition of projections they
rotate around the object 13 to be examined which is arranged along
the z axis. To this end, the gantry 18 is driven by a motor drive
16 which itself is controlled by a control unit 8'. The projections
acquired are applied to a reconstruction unit 9 for the formation
of 3D data sets and reconstruction images which are applied to the
arithmetic unit 10 again. The formation of the transformation rule
and the subsequent formation of X-ray images take place in
conjunction with the C-arm X-ray device 1 as described above and,
therefore, will not be described again.
[0034] The X-ray devices shown are merely examples of embodiments
of the invention. The invention can also be used in other X-ray
devices wherein a complete data set is to be formed from a
plurality of 3D data sets and X-ray images are to be formed
therefrom. The trajectories and their number as shown in FIG. 2 are
also given merely by way of example. The projections can also be
acquired along other trajectories or along more than two
trajectories, for example along two or more parallel full circles
or two full circles extending perpendicularly to one another.
* * * * *