Multilabel region classification and semantic linking for colon segmentation in CT colonography

Yang, X., Ye, Xujiong and Slabaugh, G. (2015) Multilabel region classification and semantic linking for colon segmentation in CT colonography. IEEE Transactions on Biomedical Engineering, 62 (3). pp. 948-959. ISSN 0018-9294

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Multilabel region classification and semantic linking for colon segmentation in CT colonography

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Accurate and automatic colon segmentation from CT images is a crucial step of many clinical applications in CT colonography, including computer-aided detection (CAD) of colon polyps, 3-D virtual flythrough of the colon, and prone/supine registration. However, the existence of adjacent air-filled organs such as the lung, stomach, and small intestine, and the collapse of the colon due to poor insufflation, render accurate segmentation of the colon a difficult problem. Extra-colonic components can be categorized into two types based on their 3-D connection to the colon: detached and attached extracolonic components (DEC and AEC, respectively). In this paper, we propose graph inference methods to remove extracolonic components to achieve a high quality segmentation. We first decompose each 3-D air-filled object into a set of 3-D regions. A classifier trained with region-level features can be used to identify the colon regions from noncolon regions. After removing obvious DEC, we remove the remaining DEC by modeling the global anatomic structure with an a priori topological constraint and solving a graph inference problem using semantic information provided by a multiclass classifier. Finally, we remove AEC by modeling regions within each 3-D object with a hierarchical conditional random field, solved by graph cut. Experimental results demonstrate that our method outperforms a purely discriminative learning method in detecting true colon regions, while decreasing extra-colonic components in challenging clinical data that includes collapsed cases.

Additional Information:Publication history on PDF: date of current version February 16, 2015
Keywords:Classification (of information), Graphic methods, Image segmentation, Semantics, Topology, Automatic colon segmentation, Computer-aided detection, Conditional random field, CT colonography, Discriminative learning, graph inference, High-quality segmentation, Topological constraints, Computerized tomography, Article, classifier, colon, computed tomographic colonography, computed tomography scanner, computer assisted radiography, discrimination learning, human, image processing, bmjgoldcheck, NotOAChecked
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
H Engineering > H673 Bioengineering
B Subjects allied to Medicine > B821 Radiography, diagnostic
Divisions:College of Science > School of Computer Science
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ID Code:16978
Deposited On:27 Mar 2015 09:23

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