Title :
Neural networks for model-based segmentation of MR brain images
Author :
Gindi, Gene ; Rangarajan, Anand ; Zubal, I. George
Author_Institution :
Dept. of Radiol., State Univ. of New York, Stony Brook, NY, USA
Abstract :
Automated segmentation of magnetic resonance (MR) brain imagery into anatomical regions is a complex task that needs contextual guidance to overcome problems associated with noise, missing data, and the overlap of features associated with different anatomical regions. In this work, the contextual information is provided as an anatomical brain atlas. The matching of atlas to image data is represented by a set of deformable contours that seek compromise fits between expected model information and image data.
Keywords :
biomedical NMR; brain; image segmentation; medical image processing; neural nets; MR brain images; anatomical brain atlas; anatomical regions; automated segmentation; contextual guidance; deformable contours; features overlap; magnetic resonance imaging; medical diagnostic imaging; missing data; model-based segmentation; noise; Biological neural networks; Biomedical imaging; Brain modeling; Computed tomography; Computer science; Image segmentation; Magnetic resonance; Medical diagnostic imaging; Radiology; Surgery;
Conference_Titel :
Biomedical Engineering Conference, 1993., Proceedings of the Twelfth Southern
Conference_Location :
New Orleans, LA, USA
Print_ISBN :
0-7803-0976-6
DOI :
10.1109/SBEC.1993.247341
