Anatomical Structure Segmentation in Liver MRI Images

2012/07/03 by G. Geethu Lakshmi, Lakshmi, G. Geethu
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #cs.CV

paper · pdf · doi:10.48550/arxiv.1207.0805

Withdrawn by author for final modification

arxiv created 2013/03/30 · arxiv updated 2013/04/02

Abstract

Segmentation of medical images is a challenging task owing to their complexity. A standard segmentation problem within Magnetic Resonance Imaging (MRI) is the task of labeling voxels according to their tissue type. Image segmentation provides volumetric quantification of liver area and thus helps in the diagnosis of disorders, such as Hepatitis, Cirrhosis, Jaundice, Hemochromatosis etc.This work deals with comparison of segmentation by applying Level Set Method,Fuzzy Level Information C-Means Clustering Algorithm and Gradient Vector Flow Snake Algorithm.The results are compared using the parameters such as Number of pixels correctly classified, and percentage of area segmented.

Related

• Automatic 3D Liver Segmentation Using Sparse Representation of Global and Local Image Information via Level Set Formulation
• Segmentation of CT images of the liver with radiology based on the water-based algorithm
• Automated liver tissues delineation techniques: A systematic survey on machine learning current trends and future orientations
• Automatic segmentation and determining radiodensity of the liver in a large-scale CT database
• Automatic Liver Segmentation from CT Images Using Deep Learning Algorithms: A Comparative Study