Colonic Polyp Detection in CT Colonography with Fuzzy Rule Based 3D Template Matching |
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Authors: | Niyazi Kilic Osman N Ucan Onur Osman |
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Institution: | (1) Engineering Faculty, Electrical and Electronics Engineering Department, Istanbul University, Avcilar, Istanbul, Turkey;(2) Ragip Gumuspala Cad. No:84, Istanbul Commerce University, 34378 Eminonu, Istanbul, Turkey |
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Abstract: | In this paper, we introduced a computer aided detection (CAD) system to facilitate colonic polyp detection in computer tomography
(CT) data using cellular neural network, genetic algorithm and three dimensional (3D) template matching with fuzzy rule based
tresholding. The CAD system extracts colon region from CT images using cellular neural network (CNN) having A, B and I templates
that are optimized by genetic algorithm in order to improve the segmentation performance. Then, the system performs a 3D template
matching within four layers with three different cell of 8 × 8, 12 × 12 and 20 × 20 to detect polyps. The CAD system is evaluated
with 1043 CT colonography images from 16 patients containing 15 marked polyps. All colon regions are segmented properly. The
overall sensitivity of proposed CAD system is 100% with the level of 0.53 false positives (FPs) per slice and 11.75 FPs per
patient for the 8 × 8 cell template. For the 12 × 12 cell templates, detection sensitivity is 100% at 0.494 FPs per slice
and 8.75 FPs per patient and for the 20 × 20 cell templates, detection sensitivity is 86.66% with the level of 0.452 FPs per
slice and 6.25 FPs per patient. |
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Keywords: | CT colonography Colon segmentation Genetic algorithm Cellular neural networks Fuzzy logic Colonic polyp detection |
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