Automated classification of colon polyps in endoscopic image data

Sebastian Gross; Stephan Palm; Jens J. W. Tischendorf; Alexander Behrens; Christian Trautwein; Til Aach

doi:10.1117/12.911177

23 February 2012 Automated classification of colon polyps in endoscopic image data

Sebastian Gross, Stephan Palm, Jens J. W. Tischendorf, Alexander Behrens, Christian Trautwein, Til Aach

Proceedings Volume 8315, Medical Imaging 2012: Computer-Aided Diagnosis; 83150W (2012) https://doi.org/10.1117/12.911177
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

Colon cancer is the third most commonly diagnosed type of cancer in the US. In recent years, however, early diagnosis and treatment have caused a significant rise in the five year survival rate. Preventive screening is often performed by colonoscopy (endoscopic inspection of the colon mucosa). Narrow Band Imaging (NBI) is a novel diagnostic approach highlighting blood vessel structures on polyps which are an indicator for future cancer risk. In this paper, we review our automated inter- and intra-observer independent system for the automated classification of polyps into hyperplasias and adenomas based on vessel structures to further improve the classification performance. To surpass the performance limitations we derive a novel vessel segmentation approach, extract 22 features to describe complex vessel topologies, and apply three feature selection strategies. Tests are conducted on 286 NBI images with diagnostically important and challenging polyps (10mm or smaller) taken from our representative polyp database. Evaluations are based on ground truth data determined by histopathological analysis. Feature selection by Simulated Annealing yields the best result with a prediction accuracy of 96.2% (sensitivity: 97.6%, specificity: 94.2%) using eight features. Future development aims at implementing a demonstrator platform to begin clinical trials at University Hospital Aachen.

Citation Download Citation

Sebastian Gross, Stephan Palm, Jens J. W. Tischendorf, Alexander Behrens, Christian Trautwein, and Til Aach "Automated classification of colon polyps in endoscopic image data", Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 83150W (23 February 2012); https://doi.org/10.1117/12.911177

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