Gastric polyps detection based on endoscopic video using modified dense micro-block difference descriptor

M. Zhdanova; V. Voronin; E. Semenishchev; O. Balabaeva; A. Zelensky

doi:10.1117/12.2571398

24 August 2020 Gastric polyps detection based on endoscopic video using modified dense micro-block difference descriptor

M. Zhdanova, V. Voronin, E. Semenishchev, O. Balabaeva, A. Zelensky

Author Affiliations +

Proceedings Volume 11511, Applications of Machine Learning 2020; 115110D (2020) https://doi.org/10.1117/12.2571398
Event: SPIE Optical Engineering + Applications, 2020, Online Only

Abstract

At the present time, medical endoscopy is the main procedure for exploring the internal cavities of the human body. The development of methods for integrating image processing and endoscopic visualization allows improving image quality and more accurately identify cancerous abnormalities. This paper proposed a new approach for the automatic detection of gastric polyp in an endoscopic video using a texture descriptor and machine learning approach. The proposed approach uses a Gabor feature and constructing a texture descriptor of dense micro-block difference (DMD). The approach improves the performance of the automatic detection of polyp in comparison with state-of-the-art methods.

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Citation Download Citation

M. Zhdanova, V. Voronin, E. Semenishchev, O. Balabaeva, and A. Zelensky "Gastric polyps detection based on endoscopic video using modified dense micro-block difference descriptor", Proc. SPIE 11511, Applications of Machine Learning 2020, 115110D (24 August 2020); https://doi.org/10.1117/12.2571398

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