An automatic method for fast and accurate liver segmentation in CT images using a shape detection level set method

2007 ◽  
Author(s):  
Jeongjin Lee ◽  
Namkug Kim ◽  
Ho Lee ◽  
Joon Beom Seo ◽  
Hyung Jin Won ◽  
...  
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
Ct Images ◽  
Automatic Method ◽  
Shape Detection ◽  
Liver Segmentation ◽  
Detection Level

scholarly journals A Hybrid Method for Pancreas Extraction from CT Image Based on Level Set Methods

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Huiyan Jiang ◽  
Hanqing Tan ◽  
Hiroshi Fujita
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
Negative Impact ◽  
Level Set Methods ◽  
Region Growing ◽  
Ct Images ◽  
Medical Image Segmentation ◽  
Initial Contour ◽  
Ct Image ◽  
Fast Marching

This paper proposes a novel semiautomatic method to extract the pancreas from abdominal CT images. Traditional level set and region growing methods that request locating initial contour near the final boundary of object have problem of leakage to nearby tissues of pancreas region. The proposed method consists of a customized fast-marching level set method which generates an optimal initial pancreas region to solve the problem that the level set method is sensitive to the initial contour location and a modified distance regularized level set method which extracts accurate pancreas. The novelty in our method is the proper selection and combination of level set methods, furthermore an energy-decrement algorithm and an energy-tune algorithm are proposed to reduce the negative impact of bonding force caused by connected tissue whose intensity is similar with pancreas. As a result, our method overcomes the shortages of oversegmentation at weak boundary and can accurately extract pancreas from CT images. The proposed method is compared to other five state-of-the-art medical image segmentation methods based on a CT image dataset which contains abdominal images from 10 patients. The evaluated results demonstrate that our method outperforms other methods by achieving higher accuracy and making less false segmentation in pancreas extraction.

Competing Front for Directed Surface Extraction from CT Images

2012 ◽  
Vol 195-196 ◽  
pp. 534-538
Author(s):  
Xue Shu Liu
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
Ct Images ◽  
Experimental Results ◽  
Second Step ◽  
Simple Method ◽  
Zero Level ◽  
Interior Surface ◽  
Surface Extraction ◽  
Speed Function

Outward directed surface extraction from imaging modalities is the first task in the design of implants. In this paper a method based on level set method is proposed to extract the directed surface from CT images. The process is composed of two steps. In the first step, Level Set method with a new speed function is employed to evolve zero level set to its destination and used to cut the desired bone part from the input CT images. In the second step, a simple method is used to extract the directed surface, usually the outward surface, from the separated bone part by removing the interior surface. The experimental results show the proposed method works well.

scholarly journals An Efficient Liver-Segmentation System Based on a Level-Set Method and Consequent Processes

2014 ◽  
Vol 07 (12) ◽  
pp. 994-1004 ◽  
Author(s):  
Walita Narkbuakaew ◽  
Hiroshi Nagahashi ◽  
Kota Aoki ◽  
Yoshiki Kubota
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
Liver Segmentation

A hybrid semi-automatic method for liver segmentation based on level-set methods using multiple seed points

2014 ◽  
Vol 113 (1) ◽  
pp. 69-79 ◽  
Author(s):  
Xiaopeng Yang ◽  
Hee Chul Yu ◽  
Younggeun Choi ◽  
Wonsup Lee ◽  
Baojian Wang ◽  
...  
Keyword(s):  
Level Set ◽  
Level Set Methods ◽  
Automatic Method ◽  
Liver Segmentation ◽  
Seed Points
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