TY - GEN
T1 - Automated 3D segmentation using deformable models and fuzzy affinity
AU - Jones, Timothy N.
AU - Metaxas, Dimitris N.
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1997.
PY - 1997
Y1 - 1997
N2 - We have developed an algorithm for segmenting objects with closed, non-intersecting boundaries, such as the heart and the lungs, that is independent of the imaging modality used (e.g., MRI, CT, echocardiography). Our method is automatic and requires as initialization a single pixel/voxel within the boundaries of the object. Existing segmentation techniques either require much more information during initialization, such as an approximation to the object's boundary, or are not robust to the types of noisy data encountered in the medical domain. By integrating region-based and physics-based modeling techniques we have devised a hybrid design that overcomes these limitations. In our experiments we demonstrate across imaging modalities, that this integration automates and significantly improves the object boundary detection results. This paper focuses on the application of our method to 3D datasets.
AB - We have developed an algorithm for segmenting objects with closed, non-intersecting boundaries, such as the heart and the lungs, that is independent of the imaging modality used (e.g., MRI, CT, echocardiography). Our method is automatic and requires as initialization a single pixel/voxel within the boundaries of the object. Existing segmentation techniques either require much more information during initialization, such as an approximation to the object's boundary, or are not robust to the types of noisy data encountered in the medical domain. By integrating region-based and physics-based modeling techniques we have devised a hybrid design that overcomes these limitations. In our experiments we demonstrate across imaging modalities, that this integration automates and significantly improves the object boundary detection results. This paper focuses on the application of our method to 3D datasets.
UR - https://www.scopus.com/pages/publications/84956853117
UR - https://www.scopus.com/pages/publications/84956853117#tab=citedBy
U2 - 10.1007/3-540-63046-5_9
DO - 10.1007/3-540-63046-5_9
M3 - Conference contribution
AN - SCOPUS:84956853117
SN - 3540630465
SN - 9783540630463
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 113
EP - 126
BT - Information Processing in Medical Imaging - 15th International Conference, IPMI 1997, Proceedings
A2 - Duncan, James
A2 - Gindi, Gene
PB - Springer Verlag
T2 - 15th International Conference on Information Processing in Medical Imaging, IPMI 1997
Y2 - 9 June 1997 through 13 June 1997
ER -