Title | Diseased region detection of longitudinal knee MRI data. |
Publication Type | Journal Article |
Year of Publication | 2013 |
Authors | Huang, Chao, Liang Shan, Cecil Charles, Marc Niethammer, and Hongtu Zhu |
Journal | Inf Process Med Imaging |
Volume | 23 |
Pagination | 632-43 |
Date Published | 2013 |
ISSN | 1011-2499 |
Keywords | Algorithms, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Knee Joint, Magnetic Resonance Imaging, Osteoarthritis, Knee, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity |
Abstract | Statistical analysis of longitudinal cartilage changes in osteoarthritis (OA) is of great importance and still a challenge in knee MRI data analysis. A major challenge is to establish a reliable correspondence across subjects within the same latent subpopulations. We develop a novel Gaussian hidden Markov model (GHMM) to establish spatial correspondence of cartilage thinning across both time and subjects within the same latent subpopulations and make statistical inference on the detection of diseased regions in each OA patient. A hidden Markov random field (HMRF) is proposed to extract such latent subpopulation structure. The EM algorithm and pseudo-likelihood method are both considered in making statistical inference. The proposed model can effectively detect diseased regions and present a localized analysis of longitudinal cartilage thickness within each latent subpopulation. Simulation studies and diseased region detection on 2D thickness maps extracted from full 3D longitudinal knee MRI Data for Pfizer Longitudinal Dataset are performed, which show that our proposed model outperforms standard voxel-based analysis. |
DOI | 10.1007/978-3-642-38868-2_53 |
Alternate Journal | Inf Process Med Imaging |
Original Publication | Diseased region detection of longitudinal knee MRI data. |
PubMed ID | 24684005 |
PubMed Central ID | PMC4012563 |
Grant List | R21 AR059890 / AR / NIAMS NIH HHS / United States R025747-01 / / PHS HHS / United States M01 RR018535 / RR / NCRR NIH HHS / United States CA142538-01 / CA / NCI NIH HHS / United States R01 MH086633 / MH / NIMH NIH HHS / United States B005149-01 / / PHS HHS / United States P01 CA142538 / CA / NCI NIH HHS / United States R01 MH091645-01A1 / MH / NIMH NIH HHS / United States MH086633 / MH / NIMH NIH HHS / United States R01 MH091645 / MH / NIMH NIH HHS / United States |
Diseased region detection of longitudinal knee MRI data.
Project: