Automatic 3D segmentation of the liver from abdominal CT images: a level-set approach

Author(s):  
Shiyan Pan ◽  
Benoit M. Dawant
2018 ◽  
Vol 23 (19) ◽  
pp. 9265-9286 ◽  
Author(s):  
Elizângela de S. Rebouças ◽  
Regis C. P. Marques ◽  
Alan M. Braga ◽  
Saulo A. F. Oliveira ◽  
Victor Hugo C. de Albuquerque ◽  
...  

2014 ◽  
Vol 556-562 ◽  
pp. 4924-4928 ◽  
Author(s):  
Feng Lian Gao ◽  
Lian Fen Huang ◽  
Jia Kun Wang ◽  
Hai Tao Shuai ◽  
Jian Jun Sun ◽  
...  

Current diagnosis with computed tomography (CT) imaging relies heavily on doctors’ clinical experience and it is difficult to accurately identify and localize lesions from thousands of CT images. Therefore, computer-aided diagnosis with automatic lesion extraction will be helpful for doctors in the diagnosis of liver diseases. In this paper, we proposed a new method for automatic liver lesion extraction from CT images by combining DRLSE (distance regularized level set evolution) and region growing. The method was applied in abdominal CT images with a single liver cancerous lesion and multiple hemangioma lesions at different locations. The results demonstrated the feasibility of our method for automatic lesion extraction with improved diagnostic accuracy and time efficiency.


Author(s):  
Mamta Raju Jotkar ◽  
Daniel Rodriguez ◽  
Bruno Marins Soares

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