TRADITIONAL POSTER - ismrm

Poster Sessions
3049. On Motion Estimation and Compensation Baseline Estimations in Dynamic Imaging: A Comparative
Study with Cine Cardiac and Contrast-Enhanced Lung Imaging
Mei-Lan Chu 1 , Jia-Shuo Hsu 1 , Hsiao-Wen Chung 1
1 Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
Estimation of the baseline is essential in compressed-sensing-based acceleration methods for MRI acquisition, as an accurate baseline estimation helps
sparsifying the residues effectively. Recent literatures suggest improved baseline estimation using adaptive regularization or motion estimation (ME) and
compensation (MC). While the suitability of these methods on other dynamic images with fast-varying contrast and morphology such as dynamic contrastenhanced
(DCE) lung imaging have not been investigated. Therefore, the purpose of this study is to explore the baseline estimation performance of the
block-matching and the phase-correlation ME/MC on both cine cardiac and DCE lung imaging, in comparison with the conventional approach.
3050. Simple Self-Gating for Compensation of Respiratory Motion Using a Spiral K-Space Trajectory
Rafael Luis O'Halloran 1 , Murat Aksoy 1 , Tobias Kober 2 , Roland Bammer 1
1 Department of Radiology, Stanford University, Stanford, CA, United States; 2 Laboratory for functional and metabolic imaging, Ecole
Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
A simple method of respiratory monitoring using the phase of the DC term of k-space collected with a spiral k-space trajectory is presented and compared
with the measurement from the respiratory bellows. The method presented is shown to be in excellent agreement with the measurement from the respiratory
bellows and reveal even cardiac pulsatility. In this work the method is used to gate a spiral-trajectory scan of the liver. The image reconstructed with the DC
phase used for gating was qualitatively similar to the one reconstructed using conventional gating. Since the image data is used for gating no additional
navigators must be acquired.
3051. Methodology for Robust Motion Correction of Complex-Valued MRI Time Series
Andrew Hahn 1 , Daniel Rowe 2
1 Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States; 2 Mathematics, Statistics, and Computer Science,
Marquette University, Milwaukee, WI
In functional MRI, subject motion during the acquisition of an image series can confound results and is generally corrected for using a variety of methods.
Because statistical models for performing complex-valued fMRI analysis are available which can provide some benefits beyond the standard magnitude-only
technique, investigation of a signal resulting from direct neuronal current involves complex-valued analysis, and recent reports have indicated potentially
valuable functionally related phase signal, performing motion correction on complex-valued time series is of interest. This work identifies the problems
facing motion correction of complex-valued images and proposes a solution for properly applying the correction.
3052. Compensation for Nonrigid Motion Using B-Spline Image Registration in Simultaneous MR-PET
Se Young Chun 1 , Sanghee Cho 1 , Tim G. Reese 2 , Bastien Guerin 1 , Xuping Zhu 1 , Jinsong Ouyang 1 , Ciprian
Catana 2 , Georges El Fakhri 1
1 Division of Nuclear Medicine & Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, United
States; 2 Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston,
MA, United States
This abstract reports preliminary results of motion corrected MR-PET reconstruction based on B-spline nonrigid image registration and compares it with
HARP based motion compensation. With a breathing phantom, we collected MR and PET data simultaneously using BrainPET prototype PET scanner
operating in the bore of a 3T TIM Trio scanner. Then we estimate the motion of a phantom using HARP and proposed B-spline based image registration
with a novel invertibility penalty. These estimated motions were used in motion compensated iterative PET reconstruction. This preliminary result shows
significant improvement of PET images for large motions.
3053. Respiratory Motion Correction of PET Using Simultaneously Acquired Tagged MRI
Timothy Gordon Reese 1 , Bastien Guérin 2 , Sanghee Cho 2 , Se Young Chun 2 , Jinsong Ouyang 2 , Xuping Zhu 2 ,
Ciprian Catana 3 , Georges El Fakhri 2
1 Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital , Boston , MA,
United States; 2 Division of Nuclear Medicine & Molecular Imaging, Department of Radiology, Massachusetts General Hospital,
Boston, MA, United States; 3 Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General
Hospital, Boston, MA, United States
As the spatial resolution of PET scanners improves, the deleterious effects of patient motion become an ever increasing limitation in PET studies. We
present our first results with incorporating clinically relevant motion information derived from MR into the PET reconstruction process. We describe our
current methods for tracking non-rigid periodic motion over the entire FOV of the MR-PET scanner, during the PET acquisition. All PET coincidences were
reconstructed in a single frame while correcting the data for motion using MRI, demonstrating feasibility on an actual MR-PET system and a significant
improvement in PET image quality.
3054. DCE-MRI Non-Rigid Kidney Registration
Michael Hofer 1 , Steven Keeling 2 , Gernot Reishofer 3 , Michael Riccabona 4 , Manuela Aschauer 3 , Rudolf
Stollberger 1
1 Institute of Medical Engineering, Graz University of Technology, Graz, Austria; 2 Institute for Mathematics and Scientific Computing,
University of Graz, Graz, Austria; 3 Department of Radiology, Medical University of Graz, Graz, Austria; 4 Department of Pediatric
Radiology, Medical University of Graz, Graz, Austria
Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is a very promising method for noninvasive assessment of renal function. To remove
the influence of motion artifacts like breathing, a novel registration approach is proposed which derives a template image series with the underlying signal
time course. This results in an independency from signal changes due to contrast media uptake. The original dynamic time series (source images) is then