A robust and fast system for CTC computer-aided detection of colorectal lesions

Slabaugh, Greg and Yang, Xiaoyun and Ye, Xujiong and Boyes, Richard and Beddoe, Gareth (2010) A robust and fast system for CTC computer-aided detection of colorectal lesions. Algorithms, 3 . pp. 21-43. ISSN 1999-4893

Full content URL: http://dx.doi.org/10.3390/a3010021

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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.

Additional Information: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
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
ID Code:7309
Deposited On:22 Jan 2013 14:30

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