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Algorithms 2010, 3(1), 21-43; doi:10.3390/a3010021
Article

A Robust and Fast System for CTC Computer-Aided Detection of Colorectal Lesions

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Received: 9 November 2009; in revised form: 14 December 2009 / Accepted: 23 December 2009 / Published: 5 January 2010
(This article belongs to the Special Issue Machine Learning for Medical Imaging)
Download PDF [2432 KB, uploaded 5 January 2010]
Abstract: We present a complete, end-to-end computer-aided detection (CAD) system for identifying lesions in the colon, imaged with computed tomography (CT). This system includes facilities for colon segmentation, candidate generation, feature analysis, and classification. The algorithms have been designed to offer robust performance to variation in image data and patient preparation. By utilizing efficient 2D and 3D processing, software optimizations, multi-threading, feature selection, and an optimized cascade classifier, the CAD system quickly determines a set of detection marks. The colon CAD system has been validated on the largest set of data to date, and demonstrates excellent performance, in terms of its high sensitivity, low false positive rate, and computational efficiency.
Keywords: CAD; colorectal lesion detection; pattern recognition CAD; colorectal lesion detection; pattern recognition
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Slabaugh, G.; Yang, X.; Ye, X.; Boyes, R.; Beddoe, G. A Robust and Fast System for CTC Computer-Aided Detection of Colorectal Lesions. Algorithms 2010, 3, 21-43.

AMA Style

Slabaugh G, Yang X, Ye X, Boyes R, Beddoe G. A Robust and Fast System for CTC Computer-Aided Detection of Colorectal Lesions. Algorithms. 2010; 3(1):21-43.

Chicago/Turabian Style

Slabaugh, Greg; Yang, Xiaoyun; Ye, Xujiong; Boyes, Richard; Beddoe, Gareth. 2010. "A Robust and Fast System for CTC Computer-Aided Detection of Colorectal Lesions." Algorithms 3, no. 1: 21-43.


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