Abstract
The implementation of Magnetic Resonance Spectroscopic Imaging (MRSI) for diagnostic imaging benefits from close integration of the lower-spatial resolution MRSI information with information from high-resolution structural MRI. Since patients can commonly move between acquisitions, it is necessary to account for possible mis-registration between the datasets arising from differences in patient positioning. In this paper we evaluate the use of 4 common multi-modality registration criteria to recover alignment between high resolution structural MRI and 3D MRSI data of the brain with sub-voxel accuracy. We explore the use of alternative MRSI water reference images to provide different types of structural information for the alignment process. The alignment accuracy was evaluated using both synthetically created MRSI and MRI data and a set of carefully collected subject image data with known ground truth spatial transformation between image volumes. The final accuracy and precision of estimates were assessed using multiple random starts of the registration algorithm. Sub voxel accuracy was found by all four similarity criteria with normalized mutual information providing the lowest target registration error for the 7 subject images. This effort supports the ongoing development of a database of brain metabolite distributions in normal subjects, which will be used in the evaluation of metabolic changes in neurological diseases.
| Original language | English (US) |
|---|---|
| Title of host publication | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
| Editors | J.M. Fitzpatrick, J.M. Reinhardt |
| Pages | 1213-1221 |
| Number of pages | 9 |
| Volume | 5747 |
| Edition | II |
| DOIs | |
| State | Published - 2005 |
| Event | Medical Imaging 2005 - Image Processing - San Diego, CA, United States Duration: Feb 13 2005 → Feb 17 2005 |
Other
| Other | Medical Imaging 2005 - Image Processing |
|---|---|
| Country | United States |
| City | San Diego, CA |
| Period | 2/13/05 → 2/17/05 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
Evaluation of sub-voxel registration accuracy between MRI and 3D MR spectroscopy of the brain. / Rousseau, F.; Maudsley, Andrew A; Ebel, A.; Darkazanli, A.; Weber, P.; Sivasankaran, K.; Yu, Y.; Studholme, C.
Progress in Biomedical Optics and Imaging - Proceedings of SPIE. ed. / J.M. Fitzpatrick; J.M. Reinhardt. Vol. 5747 II. ed. 2005. p. 1213-1221 137.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Evaluation of sub-voxel registration accuracy between MRI and 3D MR spectroscopy of the brain
AU - Rousseau, F.
AU - Maudsley, Andrew A
AU - Ebel, A.
AU - Darkazanli, A.
AU - Weber, P.
AU - Sivasankaran, K.
AU - Yu, Y.
AU - Studholme, C.
PY - 2005
Y1 - 2005
N2 - The implementation of Magnetic Resonance Spectroscopic Imaging (MRSI) for diagnostic imaging benefits from close integration of the lower-spatial resolution MRSI information with information from high-resolution structural MRI. Since patients can commonly move between acquisitions, it is necessary to account for possible mis-registration between the datasets arising from differences in patient positioning. In this paper we evaluate the use of 4 common multi-modality registration criteria to recover alignment between high resolution structural MRI and 3D MRSI data of the brain with sub-voxel accuracy. We explore the use of alternative MRSI water reference images to provide different types of structural information for the alignment process. The alignment accuracy was evaluated using both synthetically created MRSI and MRI data and a set of carefully collected subject image data with known ground truth spatial transformation between image volumes. The final accuracy and precision of estimates were assessed using multiple random starts of the registration algorithm. Sub voxel accuracy was found by all four similarity criteria with normalized mutual information providing the lowest target registration error for the 7 subject images. This effort supports the ongoing development of a database of brain metabolite distributions in normal subjects, which will be used in the evaluation of metabolic changes in neurological diseases.
AB - The implementation of Magnetic Resonance Spectroscopic Imaging (MRSI) for diagnostic imaging benefits from close integration of the lower-spatial resolution MRSI information with information from high-resolution structural MRI. Since patients can commonly move between acquisitions, it is necessary to account for possible mis-registration between the datasets arising from differences in patient positioning. In this paper we evaluate the use of 4 common multi-modality registration criteria to recover alignment between high resolution structural MRI and 3D MRSI data of the brain with sub-voxel accuracy. We explore the use of alternative MRSI water reference images to provide different types of structural information for the alignment process. The alignment accuracy was evaluated using both synthetically created MRSI and MRI data and a set of carefully collected subject image data with known ground truth spatial transformation between image volumes. The final accuracy and precision of estimates were assessed using multiple random starts of the registration algorithm. Sub voxel accuracy was found by all four similarity criteria with normalized mutual information providing the lowest target registration error for the 7 subject images. This effort supports the ongoing development of a database of brain metabolite distributions in normal subjects, which will be used in the evaluation of metabolic changes in neurological diseases.
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UR - http://www.scopus.com/inward/citedby.url?scp=23844499172&partnerID=8YFLogxK
U2 - 10.1117/12.596345
DO - 10.1117/12.596345
M3 - Conference contribution
VL - 5747
SP - 1213
EP - 1221
BT - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
A2 - Fitzpatrick, J.M.
A2 - Reinhardt, J.M.
ER -