Title :
Axon segmentation in microscopy images — A graphical model based approach
Author :
Golabchi, F. Noushin ; Brooks, Dana H.
Author_Institution :
Electr. & Comput. Eng. Dept., Northeastern Univ., Boston, MA, USA
Abstract :
Image segmentation of very large and complex microscopy images are challenging due to variability in the images and the need for algorithms to be robust, fast and able to incorporate various types of information and constraints in the segmentation model. In this paper we propose a graphical model based image segmentation framework that combines the information in images regions with the information in their boundary in a unified probabilistic formulation.
Keywords :
biological tissues; biomedical MRI; brain; image segmentation; medical image processing; neurophysiology; axon segmentation; biomedical MRI; complex microscopy imaging; graphical model based image segmentation framework; human cadaver brain tissue; image regions; large microscopy imaging; probabilistic formulation; segmentation model; spinal cord tissue; Data models; Graphical models; Image color analysis; Image segmentation; Joints; Nerve fibers; Probabilistic logic; axon segmentation; microscopy image segmentation; model based image segmentation; probabilistic graphical models;
Conference_Titel :
Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4577-1857-1
DOI :
10.1109/ISBI.2012.6235658