期刊
COMPUTERS IN BIOLOGY AND MEDICINE
卷 97, 期 -, 页码 63-73出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compbiomed.2018.04.014
关键词
Bi-Gaussian filter; 3D region growing; Hybrid active contour model; Liver vessel segmentation
类别
资金
- National Natural Science Foundation of China [61772555, 61379107, 61772556, 61172184, 61702179]
- China Postdoctoral Science Foundation [2012M521554]
- Program for Hunan Province Science and Technology Basic Construction [20131199]
- Hunan Provincial Natural Science Foundation of China [2017JJ3091]
- Scientific Research Fund of Hunan Provincial Education Department [17C0645]
This paper proposes a new automatic method for liver vessel segmentation by exploiting intensity and shape constraints of 3D vessels. The core of the proposed method is to apply two different strategies: 3D region growing facilitated by bi-Gaussian filter for thin vessel segmentation, and hybrid active contour model combined with K-means clustering for thick vessel segmentation. They are then integrated to generate final segmentation results. The proposed method is validated on abdominal computed tomography angiography (CTA) images, and obtains an average accuracy, sensitivity, specificity, Dice, Jaccard, and RMSD of 98.2%, 68.3%, 99.2%, 73.0%, 66.1%, and 2.56 mm, respectively. Experimental results show that our method is capable of segmenting complex liver vessels with more continuous and complete thin vessel details, and outperforms several existing 3D vessel segmentation algorithms.
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