Title
Liver Segmentation In Abdominal Ct Images Using Probabilistic Atlas And Adaptive 3d Region Growing
Abstract
Automatic liver segmentation plays a vital role in computer-aided diagnosis or treatment. Manual segmentation of organs is a tedious and challenging task and is prone to human errors. In this paper, we propose innovative pre-processing and adaptive 3D region growing methods with subject-specific conditions. To obtain strong edges and high contrast, we propose effective contrast enhancement algorithm then we use the atlas intensity distribution of most probable voxels in probability maps along with location before designing conditions for our 3D region growing method. We also incorporate the organ boundary to restrict the region growing. We compare our method with the label fusion of 13 organs on state-of-the-art Deeds registration method and achieved Dice score of 92.56%.
Year
DOI
Venue
2019
10.1109/EMBC.2019.8857835
2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Field
DocType
Volume
Voxel,Computer vision,Approximation algorithm,Probabilistic atlas,Computer science,Segmentation,Image segmentation,Computed tomography,Region growing,Artificial intelligence
Conference
2019
ISSN
Citations 
PageRank 
1557-170X
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Shima Rafiei132.78
Nader Karimi214532.75
Behzad Mirmahboub300.34
Kayvan Najarian426259.53
Banafsheh Felfeliyan500.34
Shadrokh Samavi623338.99
S. M. R. Soroushmehr77121.08