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A Simplified Pipeline for Motion Correction in Dual Gated Cardiac PET

  • March 2012
DOI:10.1007/978-3-642-28502-8_11
  • Conference: Bildverarbeitung für die Medizin 2012
Authors:
Lars Ruthotto at Emory University
Lars Ruthotto
Fabian Gigengack at University of Münster
Fabian Gigengack
Martin Burger at Deutsches Elektronen-Synchrotron
Martin Burger
Carsten Hermann Wolters at University of Münster
Carsten Hermann Wolters
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Abstract

Positron Emission Tomography (PET) is a nuclear imaging technique of increasing importance e.g. in cardiovascular investigations. However, cardiac and respiratory motion of the patient degrade the image quality due to acquisition times in the order of minutes. Reconstructions without motion compensation are prone to spatial blurring and affected attenuation correction. These effects can be reduced by gating, motion correction and finally summation of the transformed images. This paper describes a new and systematic approach for the correction of both cardiac and respiratory motion. Key contribution is the splitting of the motion into respiratory and cardiac components, which are then corrected individually. For the considered gating scheme the number of registration problems is reduced by a factor of 3, which considerably simplifies the motion correction pipeline compared to previous approaches. The subproblems are stabilized by averaging cardiac gates for respiratory motion estimation and vice versa. The potential of the novel pipeline is evaluated in a group study on data of 21 human patients.
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A Simplified Pipeline for Motion Correction in
Dual Gated Cardiac PET
Lars Ruthotto1, Fabian Gigengack2,3, Martin Burger4, Carsten H. Wolters5,
Xiaoyi Jiang3, Klaus P. Sch¨
afers2and Jan Modersitzki1
1Institute of Mathematics and Image Computing, University of L¨
ubeck
2European Insitute for Molecular Imaging, University of M¨
unster
3Department of Mathematics and Computer Science, University of M¨
unster
4Institute for Computational and Applied Mathematics, University of M¨
unster
5Institute of Biomagnetism and Biosignalanalysis, University of M¨
unster
lars.ruthotto@mic.uni-luebeck.de
Abstract. Positron Emission Tomography (PET) is a nuclear imaging
technique of increasing importance e.g. in cardiovascular investigations.
However, cardiac and respiratory motion of the patient degrade the image
quality due to acquisition times in the order of minutes. Reconstructions
without motion compensation are prone to spatial blurring and affected
attenuation correction. These effects can be reduced by gating, motion
correction and finally summation of the transformed images.
This paper describes a new and systematic approach for the correction
of both cardiac and respiratory motion. Key contribution is the splitting
of the motion into respiratory and cardiac components, which are then
corrected individually. For the considered gating scheme the number of
registration problems is reduced by a factor of 3, which considerably sim-
plifies the motion correction pipeline compared to previous approaches.
The subproblems are stabilized by averaging cardiac gates for respiratory
motion estimation and vice versa. The potential of the novel pipeline is
evaluated in a group study on data of 21 human patients.
1 Introduction
Positron Emission Tomography (PET) is a nuclear imaging technique that pro-
vides insight into functional processes in the body. Its fields of applications range
from oncology via neuroimaging to cardiology. Due to acquisition times in the
order of minutes, motion is a well-known problem in PET. In thoracic PET two
different types of motion degrade the image quality: respiratory and cardiac mo-
tion. Neglecting the resulting spatial mislocalization of emission events during
the reconstruction leads to blurred images and affects attenuation correction.
Gating, i.e. grouping the entire list of emission events by breathing and/or
cardiac phases reduces the extent of motion contained in each single gate [1,2]. A
downside is the higher noise level in each gate since only a small fraction of the
available events is considered. This is a severe problem in dual gating schemes,
which demand a very fine division into both respiratory and cardiac gates.
2 Ruthotto et al.
Different strategies for motion correction were proposed in the literature and
for a detailed overview see [3]. This paper follows the idea of first eliminating
the motion in the dual gated data by image registration and finally summation
of the gated images to consider all measured emission events and thereby lower
the noise level. This strategy has proven successful for respiratory motion cor-
rection [4,5] and cardiac motion correction [6]. Recently, both types of motion
were eliminated after dual gating using nonlinear mass-preserving registration
[7]. Mass-preservation is a key idea in order to cope with intensity modulations
owing to partial volume effects. Another key contribution is the discretization of
a hyperelastic regularization energy [8]. This sophisticated regularizer is manda-
tory as it achieves meaningful motion estimates and guarantees diffeomorphic
transformations even for data with high noise level and large deformations. The
algorithm was embedded into the registration toolbox FAIR that is freely avail-
able at http://www.siam.org/books/fa06/ and documented in [9].
However, the scheme in [7] is computationally very expensive since all gated
images are treated individually. This yields a total number of m·n−1 challenging
registration problems for a gating into mcardiac and nrespiratory gates.
In this paper the nature of the gating scheme is exploited to provide a system-
atic approach to motion correction and to simplify the registration pipeline. The
motion between a template gate and the reference gate is modeled as a simple
concatenation of a respiratory and a cardiac transformation under the assump-
tion that cardiac and respiratory motion are approximately independent. This
scheme reduces the number of registration tasks to m+n−2 and thus saves com-
putation times which allows finer gating schemes. In the considered 5 ×5 gating
this yields a reduction from 24 to 8 registration subproblems. Furthermore each
sub-problem is stabilized by averaging over cardiac phases in the respiratory
motion estimation and vice versa. Results for a group of 21 patients indicate the
effectiveness of the simplified approach and its positive impact on image quality.
2 Materials and Methods
2.1 Data acquisition
Data of 21 patients (19 male, 2 female; 37-76 years old) with known coronary
artery disease was acquired in a 20 minute list mode scan on a Siemens Biograph
Sensation 16 PET/CT scanner. The data was cropped to the first three minutes
to resemble a clinically feasible protocol and dual gating into 5 respiratory and 5
cardiac gates was performed, [2]. The 3D EM software EMrecon was used for
reconstruction of all data see [10]. The images are sampled with 128 ×100 ×44.
2.2 Mass-preserving hyperelastic registration
A key contribution in [7] is the incorporation of the mass-preserving property of
PET into motion correction. The idea is that the total amount of intensity of the
template image Tshould remain unchanged after registration to the reference R,
Motion correction of dual gated PET 3
which is not guaranteed for standard registration approaches. This is realized by
an intensity modulation accounting for volumetric changes given by the Jacobian
determinant of the transformation [7]. The natural distance term for density
images is the sum of squared differences yielding the image registration functional
J[y] := 1
2k(T ◦ y)·det(∇y)− Rk2+Shyper(y)
where Shyper is the hyperelastic energy [8], which was recently integrated into
FAIR: Shyper(y) = αlSlength(y) + αaSarea (y) + αvSvolume(y). It controls the
changes in length, area and volume induced by the transformation y. Since in-
finite energy is required to annihilate or enlarge a volume Shyper guarantees
the invertibility of the transformation even for large displacements and noisy
data. While this regularizer is a desirable feature in many registration tasks, it
is mandatory in this application to guarantee the preservation of mass.
2.3 Simplified registration pipeline
The used gating protocol provides 25 images denoted by Ir
cwhich are related to
5 respiratory phases r= 1, ..., 5 and 5 cardiac phases c= 1, ..., 5. The assump-
tion is that for each fixed respiratory phase rgeometric differences in Ir
1, ..., Ir
5
are only due to cardiac motion. Hence, all these cardiac phases are displaced by
the same respiratory motion yr. Respiratory motion is eliminated first from the
gated dataset as this motion shows less nonlinearities. To this end, cardiac av-
erages I1,...,I5are computed, where Ir= (P5
c=1 Ir
c)/5, and used to estimate
the respiratory displacements y1, . . . , y5based on the above mass-preserving hy-
perelastic registration. Next, respiratory motion is compensated in all 25 images.
Subsequently, I1,...,I5are computed, where Icis the average of the trans-
formed respiratory gates. These images are then used to estimate the cardiac
displacements y1, ..., y5. Note that even after removing the respiratory motion
each such gate relates to different realization of (stochastic) radioactive decay.
Hence averaging reduces the noise level even for perfect spatial alignment.
After these 4 respiratory and 4 cardiac motion estimations both types of
motion are eliminated from all 25 images. To this end yrand ycare concatenated
and the mass-preserving transformation model is applied. Finally, the motion
compensated image is obtained by summation over all gates.
3 Results
The proposed motion correction scheme is applied to the image data of 21
human patients. To minimize the geometric mismatch the mid-expiration dias-
tole gate is chosen as reference image denoted by IRef. The images are cropped
to a rectangular region of 128 ×100 ×44 voxels around the torso. Regularization
parameters are set to αl= 5, αa= 1 for length and area term as in [7]. Control
of volumetric change is tightened for respiratory by choosing αv= 100 and kept
4 Ruthotto et al.
4 Ruthotto et al.
IRef ITem and yinitial di↵erence final di↵erence
Fig. 1. Results of the 3D registration for an arbitrary chosen patient out of the 21 pa-
tients. Three orthogonal cross-sections sharing the point marked by a white crosshair
are shown. A visualization of the mid-expiration diastolic gate IRef (first col.) is com-
pared to the furthest apart end-expiratory systolic gate ITem that is visualized with
superimposed deformation y(second col.) in a small region around the heart. The
decline in absolute di↵erence (third and fourth col.) images and the increase of normal-
ized cross correlation from 0.522 to 0.681 before and after nonlinear mass-preserving
registration show the positive impact of the proposed method on image similarity.
performed on a coarse-to-fine hierarchy of levels and stopped at the second finest
discretization level (64 ⇥50 ⇥22) to improve stability against noise and speed
the correction up. The total computation time is about 8 minutes per patient
on a Linux PC with a 6 core Intel Xeon X5670@2,93 GHz using Matlab 2010b.
The volumetric change induced by the transformations serves as an indicator
to validate the injectivity of the transformation. The minimum and maximum
of the Jacobian determinant over all patients and all transformations is between
0.81 and 1.19 for respiratory and 0.55 and 1.31 for cardiac motions. Thus all
transformations including their concatenations are di↵eomorphic.
Exemplarily, the registration result is illustrated for an arbitrary chosen pa-
tient in Fig.1 using three orthogonal slice views. Presentation is restricted to the
most challenging sub-problem of registration between the end-expiration systolic
single gate no motion correction proposed motion correction
Fig. 2. Reconstruction results for an arbitrary chosen patient out of the group of 21
patients. Coronal views of the mid-expiration diastolic gate IRef (left, minimal mo-
tion blur, high noise level), reconstruction without motion correction (center, motion
blurred, acceptable noise level) and the result using the novel motion correction scheme
(right, considerably reduced motion, acceptable noise level) are visualized.
Fig. 1. Results of the 3D registration for an arbitrary chosen patient out of the 21 pa-
tients. Three orthogonal cross-sections sharing the point marked by a white crosshair
are shown. A visualization of the mid-expiration diastolic gate IRef (first col.) is com-
pared to the furthest apart end-expiratory systolic gate ITem that is visualized with
superimposed deformation y(second col.) in a small region around the heart. The
decline in absolute difference (third and fourth col.) images and the increase of normal-
ized cross correlation from 0.522 to 0.681 before and after nonlinear mass-preserving
registration show the positive impact of the proposed method on image similarity.
at the same level, αv= 10, for cardiac motion correction. Registration is per-
formed on a coarse-to-fine hierarchy of levels and stopped at the second finest
discretization level (64 ×50 ×22) to improve stability against noise and speed
the correction up. The total computation time is about 8 minutes per patient
on a Linux PC with a 6 core Intel Xeon X5670@2,93 GHz using Matlab 2010b.
The volumetric change induced by the transformations serves as an indicator
to validate the injectivity of the transformation. The minimum and maximum
of the Jacobian determinant over all patients and all transformations is between
0.81 and 1.19 for respiratory and 0.55 and 1.31 for cardiac motions. Thus all
transformations including their concatenations are diffeomorphic.
Exemplarily, the registration result is illustrated for an arbitrary chosen pa-
tient in Fig.1 using three orthogonal slice views. Presentation is restricted to the
4 Ruthotto et al.
IRef ITem and yinitial di↵erence final di↵erence
Fig. 1. Results of the 3D registration for an arbitrary chosen patient out of the 21 pa-
tients. Three orthogonal cross-sections sharing the point marked by a white crosshair
are shown. A visualization of the mid-expiration diastolic gate IRef (first col.) is com-
pared to the furthest apart end-expiratory systolic gate ITem that is visualized with
superimposed deformation y(second col.) in a small region around the heart. The
decline in absolute di↵erence (third and fourth col.) images and the increase of normal-
ized cross correlation from 0.522 to 0.681 before and after nonlinear mass-preserving
registration show the positive impact of the proposed method on image similarity.
performed on a coarse-to-fine hierarchy of levels and stopped at the second finest
discretization level (64 ⇥50 ⇥22) to improve stability against noise and speed
the correction up. The total computation time is about 8 minutes per patient
on a Linux PC with a 6 core Intel Xeon X5670@2,93 GHz using Matlab 2010b.
The volumetric change induced by the transformations serves as an indicator
to validate the injectivity of the transformation. The minimum and maximum
of the Jacobian determinant over all patients and all transformations is between
0.81 and 1.19 for respiratory and 0.55 and 1.31 for cardiac motions. Thus all
transformations including their concatenations are di↵eomorphic.
Exemplarily, the registration result is illustrated for an arbitrary chosen pa-
tient in Fig.1 using three orthogonal slice views. Presentation is restricted to the
most challenging sub-problem of registration between the end-expiration systolic
single gate no motion correction proposed motion correction
Fig. 2. Reconstruction results for an arbitrary chosen patient out of the group of 21
patients. Coronal views of the mid-expiration diastolic gate IRef (left, minimal mo-
tion blur, high noise level), reconstruction without motion correction (center, motion
blurred, acceptable noise level) and the result using the novel motion correction scheme
(right, considerably reduced motion, acceptable noise level) are visualized.
Fig. 2. Reconstruction results for an arbitrary chosen patient out of the group of 21
patients. Coronal views of the mid-expiration diastolic gate IRef (left, minimal mo-
tion blur, high noise level), reconstruction without motion correction (center, motion
blurred, acceptable noise level) and the result using the novel motion correction scheme
(right, considerably reduced motion, acceptable noise level) are visualized.
Motion correction of dual gated PET 5
Motion correction of dual gated PET 5
cardiac 1 cardiac 2 cardiac 3 cardiac 4 cardiac 5
0.5
0.6
0.7
0.8
0.9
1
Normalized Cross Correlation
Fig. 3. Motion correction results for our group study of 21 patients. Normalized cross-
correlations between the 24 template gates and the reference gate are shown before
(gray) and after (black) motion correction in a box plot. The considerable increase of
NCC shows the e↵ectiveness and robustness of the new method.
0.81 and 1.19 for respiratory and 0.55 and 1.31 for cardiac motions. Thus all
transformations including their concatenations are di↵eomorphic.
Exemplarily, the registration result is illustrated for an arbitrary chosen pa-
tient in Fig.1 using three orthogonal slice views. Presentation is restricted to the
most challenging sub-problem of registration between the end-expiration systolic
gate and the mid-expiration diastolic reference gate. The di↵erence images before
and after registration clearly show the considerably improved image similarity.
Furthermore the transformation y5
2- obtained by concatenating the respiratory
motion y5and the cardiac component y2is smooth and regular.
The positive impact of the new strategy on image quality is illustrated for
the same dataset in Fig. 2 in a coronal view. The e↵ect of gating - minimal
motion blur, but high noise level - is visible in the reference gate (left). The not
motion-corrected reconstruction (center) shows acceptable noise level, but the
hearts contour is motion-blurred. Both advantages - minimal motion blur and
acceptable noise level - are combined by the resulting image of the new method.
The improvement of image similarity after motion correction is presented in
Fig. 3 for the whole group of 21 patients. Normalized cross-correlations (NCC)
between MathcalIRef and the 24 template gates computed in a rectangular re-
gion around the heart for all patients are illustrated in a box plot. A considerable
increase of NCC can be seen by comparing the gray (before registration) and
black (after registration) boxes and whiskers.
4 Discussion
This paper presents an systematic approach to cardiac and respiratory motion
correction in dual gated thoracic PET. The main contribution is the simplifica-
tion of the processing pipeline achieved by a splitting of the displacement into a
respiration and cardiology component and individually correction of both e↵ects
in the dual gated dataset. A considerably lower number of registration problems
Fig. 3. Motion correction results for our group study of 21 patients. Normalized cross-
correlations between the 24 template gates and the reference gate are shown before
(gray) and after (black) motion correction in a box plot. The considerable increase of
NCC shows the effectiveness and robustness of the new method.
most challenging sub-problem of registration between the end-expiration systolic
gate and the mid-expiration diastolic reference gate. The difference images before
and after registration clearly show the considerably improved image similarity.
Furthermore the transformation y5
2- obtained by concatenating the respiratory
motion y5and the cardiac component y2is smooth and regular.
The positive impact of the new strategy on image quality is illustrated for
the same dataset in Fig. 2 in a coronal view. The effect of gating - minimal
motion blur, but high noise level - is visible in the reference gate (left). The not
motion-corrected reconstruction (center) shows acceptable noise level, but the
hearts contour is motion-blurred. Both advantages - minimal motion blur and
acceptable noise level - are combined by the resulting image of the new method.
The improvement of image similarity after motion correction is presented in
Fig. 3 for the whole group of 21 patients. Normalized cross-correlations (NCC)
between IRef and the 24 template gates computed in a rectangular region around
the heart for all patients are illustrated in a box plot. A considerable increase of
NCC can be seen by comparing the gray (before registration) and black (after
registration) boxes and whiskers.
4 Discussion
This paper presents an systematic approach to cardiac and respiratory motion
correction in dual gated thoracic PET. The main contribution is the simplifica-
tion of the processing pipeline achieved by a splitting of the displacement into a
respiration and cardiology component and individually correction of both effects
in the dual gated dataset. A considerably lower number of registration problems
need to be solved, which are stabilized by averaging cardiac gates for respira-
tory correction and vice versa. The correction results for a group of 21 patients
suggest that the underlying assumption that cardiac and respiratory motion are
independent is approximately fulfilled for our data.
6 Ruthotto et al.
The presented pipeline is in principle compatible with existing approaches to
cardiac and respiratory motion correction techniques [6,4,5,7]. Here, a nonlinear
mass-preserving approach is chosen as it is well-suited for the registration of
density images such as PET, [7]. The preservation of mass can be ensured under
certain assumptions including the invertibility of the transformation. Therefore
an implementation of a hyperelastic regularizer [8], which is integrated in the
freely available toolbox FAIR [9], is used. This regularizer guarantees diffeomor-
phic solutions of the problem, but still allows large and flexible transformations.
Individual treatment of respiratory and cardiac motion seems reasonable as
both types of motion are very different in nature. While the further is almost
locally rigid, the hearts contraction tends to be more flexible. In the proposed
pipeline this can be addressed by e.g. the choice of different regularization pa-
rameters for both types as done in this work. This enforces a smaller range of
the volumetric changes due to respiratory motion for our data.
Despite the considerably reduced distance, the heart structure is still visible
in the final difference images, see Fig.1. The registration could be improved
by performing a number of outer loops over respiratory and cardiac motion
correction to be investigated in future work.
The very promising results presented in this paper mark a next step towards
clinical applicability of motion correction methods in thoracic PET. With the
simplified registration pipeline the quality of motion correction can be further
improved as finer subdivision schemes become feasible.
5 Acknowledgements
The authors thank Otmar Schober from the Department of Nuclear Medicine at
the University of M¨
unster for providing the interesting data.
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... For example, Brune replaced the brightness 339 constancy by a mass-conservation constraint; see [13]. This gives the optical flow pendant to 340 mass-preserving image registration schemes; see [30,60,61] and sections "Distance Functionals" 341 Handbook of Mathematical Methods in Imaging DOI 10.1007/978-3-642-27795-5_39-2 © Springer Science+Business Media New York 2014 and "Motion Correction of Cardiac PET". Further, rigidity constraints have been enforced in 342 optical flow settings in [50]. ...
... For each gate, a 918 reconstruction is computed which shows less motion blur, but is also based on fewer counts and 919 consequently of degraded quality as signal to noise has been reduced. To take full advantage of 920 all measurements, the individual reconstructions are aligned using image registration and finally 921 fused [30,61]. ...
... Fig. 9b. A smooth 948 and motion-corrected reconstruction is obtained by following the pipeline suggested in [61] and 949 averaging the aligned images. Here a much sharper and clearer image can be reconstructed; cf. ...
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... For example, Brune replaced the brightness 339 constancy by a mass-conservation constraint; see [13]. This gives the optical flow pendant to 340 mass-preserving image registration schemes; see [30,60,61] and sections "Distance Functionals" 341 Handbook of Mathematical Methods in Imaging DOI 10.1007/978-3-642-27795-5_39-2 © Springer Science+Business Media New York 2014 and "Motion Correction of Cardiac PET". Further, rigidity constraints have been enforced in 342 optical flow settings in [50]. ...
... For each gate, a 918 reconstruction is computed which shows less motion blur, but is also based on fewer counts and 919 consequently of degraded quality as signal to noise has been reduced. To take full advantage of 920 all measurements, the individual reconstructions are aligned using image registration and finally 921 fused [30,61]. ...
... Fig. 9b. A smooth 948 and motion-corrected reconstruction is obtained by following the pipeline suggested in [61] and 949 averaging the aligned images. Here a much sharper and clearer image can be reconstructed; cf. ...
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... For example, Brune replaced the brightness constancy by a mass-conservation constraint; see [13]. This gives the optical flow pendant to mass-preserving image registration schemes; see [74,33,75] and Sections 2.2 and 5.1. Further, rigidity constraints have been enforced in optical flow settings in [54]. ...
... To the best of our knowledge, we presented the first method that simultaneously corrects both types of motion using a dual gating in [33]. We presented a simplified registration pipeline that reduced the number of registration problems in [75]. ...
... We gave a detailed discussion of a mass-preserving distance functional. This distance functional has desirable properties for the registration of density images like, for instance, in Positron Emission Tomography; see [74,33,75] and Section 5.1. However additional regularization is required to guarantee existence of solutions and to ensure mass-preservation. ...
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... Crucial for the proof is controlling sequences of functions after transformations ρ k (y k ) det(∇y k ) with ρ k , y k beeing weak-* convergent sequences resulting from coercivity properties. Before actually presenting our central theorem on this convergence, we define weak-* convergence for the transformation as follows (compare [50]). ...
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Conference Paper
  • Oct 2012
The aim of this work is to present an advanced motion correction pipeline for dual gating based on motion compensation. The pipeline is robust against noise and uses the whole statistic for the final image. We extend motion compensation by motion compensated reconstructions which allow a much finer dual gating for maximal reduction of motion artifacts. Further, mass-preserving motion estimation based on spline transformations is performed motion estimation.
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A Hyperelastic Regularization Energy for Image Registration
Article
Full-text available
  • Jan 2013
Image registration is one of the most challenging problems in image processing, where ill-posedness arises due to noisy data as well as non-uniqueness and hence the choice of regularization is crucial. This paper presents hyperelasticity as a regularizer and introduces a new and stable numerical implementation. On one hand, hyperelastic registration is an appropriate model for large and highly nonlinear deformations, for which a linear elastic model needs to fail. On the other hand, the hyperelastic regularizer yields very regular and diffeomorphic transformations. While hyperelasticity might be considered as just an additional outstanding regularization option for some applications, it becomes inevitable for applications involving higher order distance measures like mass-preserving registration. The paper gives a short introduction to image registration and hyperelasticity. The hyperelastic image registration problem is phrased in a variational setting and an existence proof is provided. The focus of the paper, however, is on a robust numerical scheme. A key challenge is an unbiased discretization of hyperelasticity, which enables the numerical monitoring of variations of length, surface and volume of infinitesimal reference elements. We resolve this issue by using a nodal based discretization with a special tetrahedral partitioning. The potential of the hyperelastic registration is demonstrated in a direct comparison with a linear elastic registration on an academical example. The paper also presents a real life application from 3D Positron Emission Tomography (PET) of the human heart which requires mass-preservation and thus hyperelastic registration is the only option.
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Motion correction of cardiac PET using mass-preserving registration
Conference Paper
Full-text available
  • Dec 2010
Cardiac motion leads to image quality degradation in positron emission tomography (PET). In the literature gated list-mode acquisition along with motion estimation techniques, such as optical flow or image registration, proved successful for respiratory motion correction. Cardiac gated PET images, however, are affected by the partial volume effect (PVE) which is expressed in strongly varying local intensities. This fact complicates the motion estimation process. To overcome this problem, the mass-preserving nature of PET images is identified and included into the image registration problem. We show that our mass-preserving registration approach allows cardiac motion correction with high accuracy due to realistic motion estimates. In addition, neglecting the mass-preserving property of PET is proven to entail unrealistic results.
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Motion Correction in Dual Gated Cardiac PET Using Mass-Preserving Image Registration
Article
Full-text available
Respiratory and cardiac motion leads to image degradation in positron emission tomography (PET) studies of the human heart. In this paper we present a novel approach to motion correction based on dual gating and mass-preserving hyperelastic image registration. Thereby, we account for intensity modulations caused by the highly nonrigid cardiac motion. This leads to accurate and realistic motion estimates which are quantitatively validated on software phantom data and carried over to clinically relevant data using a hardware phantom. For patient data, the proposed method is first evaluated in a high statistic (20 min scans) dual gating study of 21 patients. It is shown that the proposed approach properly corrects PET images for dual-cardiac as well as respiratory-motion. In a second study the list mode data of the same patients is cropped to a scan time reasonable for clinical practice (3 min). This low statistic study not only shows the clinical applicability of our method but also demonstrates its robustness against noise obtained by hyperelastic regularization.
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List Mode-Driven Cardiac and Respiratory Gating in PET
Article
Full-text available
  • Apr 2009
Gating methods acquiring biosignals (such as electrocardiography [ECG] and respiration) during PET enable one to reduce motion effects that potentially lead to image blurring and artifacts. This study evaluated different cardiac and respiratory gating methods: one based on ECG signals for cardiac gating and video signals for respiratory gating; 2 others based on measured inherent list mode events. Twenty-nine patients with coronary artery disease underwent a 20-min ECG-gated single-bed list mode PET scan of the heart. Of these, 17 were monitored by a video camera registering a marker on the patient's abdomen, thus capturing the respiratory motion for PET gating (video method). Additionally, respiratory and cardiac gating information was deduced without auxiliary measurements by dividing the list mode stream in 50-ms frames and then either determining the number of coincidences (sensitivity method) or computing the axial center of mass and SD of the measured counting rates in the same frames (center-of-mass method). The gated datasets (respiratory and cardiac gating) were reconstructed without attenuation correction. Measured wall thicknesses, maximum displacement of the left ventricular wall, and ejection fraction served as measures of the exactness of gating. All methods successfully captured respiratory motion and significantly decreased motion-induced blurring in the gated images. The center-of-mass method resulted in significantly larger left ventricular wall displacements than did the sensitivity method (P < 0.02); other differences were nonsignificant. List mode-based cardiac gating was found to work well for patients with high (18)F-FDG uptake when the center-of-mass method was used, leading to an ejection fraction correlation coefficient of r = 0.95 as compared with ECG-based gating. However, the sensitivity method did not always result in valid cardiac gating information, even in patients with high (18)F-FDG uptake. Our study demonstrated that valid gating signals during PET scans cannot be obtained only by tracking the external motion or applying an ECG but also by simply analyzing the PET list mode stream on a frame-by-frame basis.
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Four-dimensional processing of deformable cardiac PET data
Article
A four-dimensional deformable motion algorithm is described for use in the motion compensation of gated cardiac positron emission tomography. The algorithm makes use of temporal continuity and a non-uniform elastic material model to provide improved estimates of heart motion between time frames. Temporal continuity is utilized in two ways. First, incremental motion fields between adjacent time frames are calculated to improve estimation of long-range motion between distant time frames. Second, a consistency criterion is used to insure that the image match between distant time frames is consistent with the deformations used to match adjacent time frames. The consistency requirement augments the algorithm's ability to estimate motion between noisy time frames, and the concatenated incremental motion fields improve estimation for large deformations. The estimated motion fields are used to establish a voxel correspondence between volumes and to produce a motion-compensated composite volume.
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EMRECON: An expectation maximization based image reconstruction framework for emission tomography data
Article
  • Oct 2011
We present a flexible image reconstruction framework for emission tomography data called EMRECON. The software includes multiple expectation maximization based reconstruction algorithms as well as support for several scanner geometries. In order to implement novel reconstruction techniques (e.g. TV-based regularization or combined reconstruction and motion correction) or scanner models, full access to every stage of the reconstruction pipeline is vital. EMrecon is fully open and well-documented, thus permits testing without the need to care about data formats or standard reconstruction and data correction algorithms. Due to the GATE-like syntax new scanner geometries, including an exact definition of each single crystal, can be added easily. The parallel (multi-core) C implementation was successfully tested on several Linux distributions. This makes EMRECON a useful tool for the development of new reconstruction algorithms and also serves as a platform for testing different scanner geometries.
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FAIR: Flexible Algorithms for Image Registration
Article
  • Sep 2008
This book really shows how registration works: the flip-book appearing at the top right corners shows a registration of a human knee from bent to straight position (keeping bones rigid). Of course, the book also provides insight into concepts and practical tools. The presented framework exploits techniques from various fields such as image processing, numerical linear algebra, and optimization. Therefore, a brief overview of some preliminary literature in those fields is presented in the introduction (references [1–51]), and registration-specific literature is assembled at the end of the book (references [52–212]). Examples and results are based on the FAIR software, a package written in MATLAB. The FAIR software, as well as a PDF version of this entire book, can be freely downloaded from www.siam.org/books/fa06. This book would not have been possible without the help of Bernd Fischer, Eldad Haber, Claudia Kremling, Jim Nagy, and the Safir Research Group from Lübeck: Sven Barendt, Björn Beuthin, Konstantin Ens, Stefan Heldmann, Sven Kabus, Janine Olesch, Nils Papenberg, Hanno Schumacher, and Stefan Wirtz. I'm also indebted to Sahar Alipour, Reza Heydarian, Raya Horesh, Ramin Mafi, and Bahram Marami Dizaji for improving the manuscript.
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Motion Correction and Attenuation Correction for Respiratory Gated PET Images
Article
Positron emission tomography (PET) is a molecular imaging technique which provides important functional information about the human body. However, thoracic PET images are often substantially degraded by respiratory motion, which adversely impacts on subsequent diagnosis. In this paper, a motion correction and attenuation correction method is proposed to correct for motion in respiratory gated PET images and to yield an accurate distribution of the radioactivity concentration. Experimental results show that this method can effectively correct for motion and improve PET image quality. The method is able to provide improved diagnostic information without increasing the acquisition time or the radiation burden.
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Regularized B-spline deformable registration for respiratory motion correction in PET images
Article
  • May 2009
A major challenge in thoracic PET imaging is respiratory motion, which degrades image quality to the extent that it can affect subsequent diagnosis and patient management. This paper presents an approach to overcoming this problem using a deformable registration algorithm for respiratory gated PET images. Registration is based entirely on PET images without increasing the radiation burden. A Markov random field regularizer is introduced to the registration, which penalizes noisy deformation fields. Experimental results on both simulated and real data show that regularized registration effectively suppresses the noise in images, yielding satisfactory deformation fields. In addition, motion correction using the registration algorithm significantly improves the quality of PET images.
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