Improved automatic liver segmentation of a contrast enhanced CT image

Authors:
Kyung-Sik Seo;Jong-An Park
Affiliations:
Dept. of Information & Communications Engineering, Chosun University, Gwangju, Korea;Dept. of Information & Communications Engineering, Chosun University, Gwangju, Korea
Venue:
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part I
Year:
2005

Citing 6
Cited 1

Digital Image Processing: PIKS Inside

Digital Image Processing: PIKS Inside
Digital Image Processing Algorithms and Applications

Digital Image Processing Algorithms and Applications
Computer Vision

Computer Vision
Digital Image Processing

Digital Image Processing
Automatic segmentation of liver region based on extracted blood vessels

Systems and Computers in Japan
Efficient liver segmentation based on the spine

ADVIS'04 Proceedings of the Third international conference on Advances in Information Systems

Survey on liver CT image segmentation methods

Artificial Intelligence Review

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents an improved automatic liver segmentation method using a left partial histogram threshold (LPHT) algorithm. The LPHT algorithm removes other neighboring abdominal organs regardless of pixel variation of contrast enhanced computed tomography (CE-CT) images. After histogram transformation, adaptive multi-modal threshold is used to find the range of gray-level values of the liver structure. The LPHT algorithm is performed to removing other neighboring organs. Then, binary morphological filtering is processed to remove unnecessary objects and smooth the boundary. 48 CE-CT slices of twelve patients were selected to test the proposed automatic liver segmentation. As evaluation methods, normalized average area and area error rate were used. The results of experiments show similar performance between the proposed algorithm and the manual method by a medical doctor.