Segmentation of a Vector Field: Dominant Parameter and Shape Optimization
Journal of Mathematical Imaging and Vision
Organ pose distribution model and an MAP framework for automated abdominal multi-organ localization
MIAR'10 Proceedings of the 5th international conference on Medical imaging and augmented reality
Computation and evaluation of medial surfaces for shape representation of abdominal organs
MICCAI'11 Proceedings of the Third international conference on Abdominal Imaging: computational and Clinical Applications
Optimal medial surface generation for anatomical volume representations
MICCAI'12 Proceedings of the 4th international conference on Abdominal Imaging: computational and clinical applications
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Extensive recent work has taken place on the construction of probabilistic atlases of anatomical organ. We propose a probabilistic atlas of ten major abdominal organs which retains structural variability by using a size-preserving affine registration, and normalizes the physical organ locations to an anatomical landmark. Restricting the degrees of freedom in the transformation, the bias from the reference data is minimized, in terms of organ shape, size and position. Additionally, we present a scheme for the study of anatomical variability within the abdomen, including the clusterization of the modes of variation. The analysis of deformation fields showed a strong correlation with anatomical landmarks and known mechanical deformations in the abdomen. The atlas and its dependencies represent a potentially important research tool for abdominal diagnosis, modeling and soft tissue interventions.