TY - JOUR
T1 - Automatic three-dimensional segmentation of MR images applied to the rat uterus - art. no. 61430R
AU - Akselrod-Ballin, Ayelet
AU - Eyal, Erez
AU - Galun, Meirav
AU - Furman-Haran, Edna
AU - Gomori, John Moshe
AU - Basri, Ronen
AU - Degani, Hadassa
AU - Brandt, Achi
PY - 2006
Y1 - 2006
N2 - 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.
AB - 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.
U2 - 10.1117/12.653371
DO - 10.1117/12.653371
M3 - Meeting Abstract
SN - 0277-786X
VL - 6143
SP - R1430-R1430
JO - Medical Imaging 2006: Physiology, Function, And Structure From Medical Images Pts 1 And 2
JF - Medical Imaging 2006: Physiology, Function, And Structure From Medical Images Pts 1 And 2
T2 - Medical Imaging 2006 Conference
Y2 - 12 February 2006 through 14 February 2006
ER -