Cube propagation for focal brain atrophy estimation
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Cube propagation for focal brain atrophy estimation. / Pai, Akshay Sadananda Uppinakudru; Sørensen, Lauge; Darkner, Sune; Mysling, Peter; Jørgensen, Dan Richter; Dam, Erik B.; Lillholm, Martin; Oh, Joonmi; Chen, Gennan; Suhy, Joyce; Sporring, Jon; Nielsen, Mads.
2013 IEEE 10th International Symposium on Biomedical Imaging. IEEE, 2013. p. 402-405.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Cube propagation for focal brain atrophy estimation
AU - Pai, Akshay Sadananda Uppinakudru
AU - Sørensen, Lauge
AU - Darkner, Sune
AU - Mysling, Peter
AU - Jørgensen, Dan Richter
AU - Dam, Erik B.
AU - Lillholm, Martin
AU - Oh, Joonmi
AU - Chen, Gennan
AU - Suhy, Joyce
AU - Sporring, Jon
AU - Nielsen, Mads
N1 - Conference code: 10
PY - 2013
Y1 - 2013
N2 - Precise and robust whole brain, ventricle, and hippocampal atrophy measurements are important as they serve as biomarkers for Alzheimer’s disease. They are used as secondary outcomes in drug trials, and they correlate with the cognitive scores. When two successive scans are non-linearly aligned by registration, the volume change in a region of interest (ROI) is typically computed by Jacobian integration (JI), volumetric meshing (VM), or surface based methods like surface triangulation (ST) or surface flux (SF). JI and VM offer the possibility of a voxel-by-voxel atrophy measure for visualization or localization of atrophy and subsequent summing to an ROI measure of atrophy. ST and SF only offer whole ROI atrophy measures. JI and SF suffer from a lack of precision originating from respectively approximating a space and a time integral by a finite sum. VM suffers from a high computational burden and the ST from the lack of localization. In this paper we present the cube propagation (CP) algorithm having numerical precision as VM, offering the localization as JI and VM, but computational simplicity as the ST and SF. We demonstrate superior numerical precision to the the commonly used JI.
AB - Precise and robust whole brain, ventricle, and hippocampal atrophy measurements are important as they serve as biomarkers for Alzheimer’s disease. They are used as secondary outcomes in drug trials, and they correlate with the cognitive scores. When two successive scans are non-linearly aligned by registration, the volume change in a region of interest (ROI) is typically computed by Jacobian integration (JI), volumetric meshing (VM), or surface based methods like surface triangulation (ST) or surface flux (SF). JI and VM offer the possibility of a voxel-by-voxel atrophy measure for visualization or localization of atrophy and subsequent summing to an ROI measure of atrophy. ST and SF only offer whole ROI atrophy measures. JI and SF suffer from a lack of precision originating from respectively approximating a space and a time integral by a finite sum. VM suffers from a high computational burden and the ST from the lack of localization. In this paper we present the cube propagation (CP) algorithm having numerical precision as VM, offering the localization as JI and VM, but computational simplicity as the ST and SF. We demonstrate superior numerical precision to the the commonly used JI.
U2 - 10.1109/ISBI.2013.6556497
DO - 10.1109/ISBI.2013.6556497
M3 - Article in proceedings
SN - 978-1-4673-6454-6
SP - 402
EP - 405
BT - 2013 IEEE 10th International Symposium on Biomedical Imaging
PB - IEEE
Y2 - 7 April 2013 through 11 April 2013
ER -
ID: 45566067