Title :
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
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;
Conference_Titel :
Complex, Intelligent and Software Intensive Systems, 2008. CISIS 2008. International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-0-7695-3109-0
DOI :
10.1109/CISIS.2008.135