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Proceedings Paper

Automatic three-dimensional segmentation of MR images applied to the rat uterus
Author(s): Ayelet Akselrod-Ballin; Erez Eyal; Meirav Galun; Edna Furman-Haran; John Moshe Gomori; Ronen Basri; Hadassa Degani; Achi Brandt
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Paper Abstract

We introduce an automatic 3D multiscale automatic segmentation algorithm for delineating specific organs in Magnetic Resonance images (MRI). The algorithm can process several modalities simultaneously, and handle both isotropic and anisotropic data in only linear time complexity. It produces a hierarchical decomposition of MRI scans. During this segmentation process a rich set of features describing the segments in terms of intensity, shape and location are calculated, reflecting the formation of the hierarchical decomposition. We show that this method can delineate the entire uterus of the rat abdomen in 3D MR images utilizing a combination of scanning protocols that jointly achieve high contrast between the uterus and other abdominal organs and between inner structures of the rat uterus. Both single and multi-channel automatic segmentation demonstrate high correlation to a manual segmentation. While the focus here is on the rat uterus, the general approach can be applied to recognition in 2D, 3D and multi-channel medical images.

Paper Details

Date Published: 13 March 2006
PDF: 9 pages
Proc. SPIE 6143, Medical Imaging 2006: Physiology, Function, and Structure from Medical Images, 61430R (13 March 2006); doi: 10.1117/12.653371
Show Author Affiliations
Ayelet Akselrod-Ballin, Weizmann Institute of Science (Israel)
Erez Eyal, Weizmann Institute of Science (Israel)
Meirav Galun, Weizmann Institute of Science (Israel)
Edna Furman-Haran, Weizmann Institute of Science (Israel)
John Moshe Gomori, Hadassah Univ. Medical Ctr. (Israel)
Ronen Basri, Weizmann Institute of Science (Israel)
Hadassa Degani, Weizmann Institute of Science (Israel)
Achi Brandt, Weizmann Institute of Science (Israel)


Published in SPIE Proceedings Vol. 6143:
Medical Imaging 2006: Physiology, Function, and Structure from Medical Images
Armando Manduca; Amir A. Amini, Editor(s)

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