Abstract
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. © 2009 Springer-Verlag.
Original language | English |
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Title of host publication | Medical Image Computing and Computer-Assisted Intervention |
Number of pages | 9 |
Volume | 5761 |
Publisher | Springer-verlag Berlin |
Publication date | 2009 |
Pages | 272-280 |
ISBN (Print) | 978-3-642-04267-6 |
DOIs | |
Publication status | Published - 2009 |
Externally published | Yes |
Event | 12th International Conference on Medical Image Computing and Computer-Assisted Intervention - Imperial College, London, United Kingdom Duration: 20 Sept 2009 → 24 Sept 2009 Conference number: 12 |
Conference
Conference | 12th International Conference on Medical Image Computing and Computer-Assisted Intervention |
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Number | 12 |
Location | Imperial College |
Country/Territory | United Kingdom |
City | London |
Period | 20/09/2009 → 24/09/2009 |
Series | Lecture Notes in Computer Science |
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ISSN | 0302-9743 |
Keywords
- Differential equations
- Medical computing
- Image segmentation