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

fYear

2012

fDate

2-5 May 2012

Firstpage

756

Lastpage

759

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on

Conference_Location

Barcelona

ISSN

1945-7928

Print_ISBN

978-1-4577-1857-1

Type

conf

DOI

10.1109/ISBI.2012.6235658

Filename

6235658