Hilbert-Huang transform-based video analysis for detecting colon polyps using composite similarity measure
by Mainak Biswas; Debangshu Dey
International Journal of Telemedicine and Clinical Practices (IJTMCP), Vol. 1, No. 2, 2015

Abstract: The third leading cause of deaths from cancer is colorectal cancer (10% men and 9.2% in women). The only prevention is to detect and remove the colon polyps during optical colonoscopy. Hilbert-Huang transformation is an adaptive data driven technique. Nucleus of HHT is empirical mode decomposition. In this work, separate sets of training and testing samples are opted. This paper proposes bi-dimensional statistical empirical mode decomposition-based colon polyp detection strategy, wherein a composite similarity measure has been used. Few samples are randomly chosen for training database, remaining samples make the testing database. The proposed method is implemented on sequences of sample images from an optical colonoscopy video database provided by American College of Gastroenterology. Principal component analysis-based feature extraction is used in this work, as it reduces the dimensions efficiently from the main object. The obtained results demonstrate the achieved improvement in the recognition rates, in comparison with other procedures.

Online publication date: Tue, 09-Jun-2015

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