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Joint Segmentation of Image Ensembles via Latent Atlases
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Institution: |
1Computer Science and Artificial Intelligence Laboratory, MIT, USA 2Department of Information and Computer Science, Helsinki University of Technology, Finland 3Department of Neurology, MGH, Harvard Medical School, USA 4Brigham and Womens Hospital, Harvard Medical School, USA |
Publisher: |
Int Conf Med Image Comput Comput Assist Interv. MICCAI 2009 |
Publication Date: |
Sep-2009 |
Citation: |
Int Conf Med Image Comput Comput Assist Interv. 2009;12(Pt 1):272–280. |
Keywords: |
Projects:LatentAtlasSegmentation |
Appears in Collections: |
NA-MIC, NAC, NCIGT |
Sponsors: |
NIH NIBIB NAMIC U54 EB005149 NIH NCRR NAC P41 RR13218 NIH NINDS R01 NS051826 NIH NCRR mBIRN U24 RR021382 NSF CAREER Award 0642971 |
Generated Citation: |
Riklin Raviv T, Van Leemput K, Wells III W, Golland P. Joint Segmentation of Image Ensembles via Latent Atlases. Int Conf Med Image Comput Comput Assist Interv. 2009;12(Pt 1):272–280. |
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| Paper: | Download, View online |
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Spatial priors, such as probabilistic atlases, play an important role in MRI segmentation. However, the availability of comprehensive, reliable and suitable manual segmentations for atlas construction is limited. We therefore propose a joint segmentation of corresponding, aligned structures in the entire population that does not require a probability atlas. Instead, a latent atlas, initialized by a single manual segmentation, is inferred from the evolving segmentations of the ensemble. The proposed method is based on probabilistic principles but is solved using partial differential equations (PDEs) and energy minimization criteria. We evaluate the method by segmenting 50 brain MR volumes. Segmentation accuracy for cortical and subcortical structures approaches the quality of state-of-the-art atlas-based segmentation results, suggesting that the latent atlas method is a reasonable alternative when existing atlases are not compatible with the data to be processed.
Additional Material
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Riklin-Raviv-MICCAI2009-fig2.jpg (156.478kB)