Segmentation of the Liver from Abdominal CT Using Markov Random Field Model and GVF Snakes

Author

Alomari, Raja S. ; Kompalli, Suryaprakash ; Chaudhary, Vipin

Author_Institution

Dept. of Comput. Sci. & Eng., State Univ. of New York, Buffalo, NY

fYear

2008

fDate

4-7 March 2008

Firstpage

293

Lastpage

298

Abstract

Liver segmentation from scans of the abdominal area is an important step in several diagnostic processes. CT scans of the abdominal area contain several organs in close proximity exhibiting similar image characteristics. In this paper, we present preliminary results on an algorithm that uses Markov random fields to obtain an initial contour of the liver. Gradient vector fields (GVF) and active contours are used to refine the initial estimate and segment the liver. Tests are reported on 13 clinical cases using a similarity metric that combines area and space.

Keywords

Markov processes; computerised tomography; gradient methods; image segmentation; liver; medical image processing; random processes; Markov random field model; abdominal CT scan; active contour; gradient vector field; liver segmentation; Abdomen; Active contours; Competitive intelligence; Computed tomography; DICOM; Histograms; Image segmentation; Liver; Markov random fields; Software systems; GVF Snakes; Markov Random Fields; X-ray CT; database construction; evaluation; liver segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Complex, Intelligent and Software Intensive Systems, 2008. CISIS 2008. International Conference on

Conference_Location

Barcelona

Print_ISBN

978-0-7695-3109-0

Type

conf

DOI

10.1109/CISIS.2008.135

Filename

4606695