Computer assisted gastric abnormalities detection using hybrid texture descriptors for chromoendoscopy images

Computer Methods and Programs in Biomedicine
Hussam AliMubashir Husain Rehmani

Abstract

The early diagnosis of stomach cancer can be performed by using a proper screening procedure. Chromoendoscopy (CH) is an image-enhanced video endoscopy technique, which is used for inspection of the gastrointestinal-tract by spraying dyes to highlight the gastric mucosal structures. An endoscopy session can end up with generating a large number of video frames. Therefore, inspection of every individual endoscopic-frame is an exhaustive task for the medical experts. In contrast with manual inspection, the automated analysis of gastroenterology images using computer vision based techniques can provide assistance to endoscopist, by finding out abnormal frames from the whole endoscopic sequence. In this paper, we have presented a new feature extraction method named as Gabor-based gray-level co-occurrence matrix (G2LCM) for computer-aided detection of CH abnormal frames. It is a hybrid texture extraction approach which extracts a combination both local and global texture descriptors. Moreover, texture information of a CH image is represented by computing the gray level co-occurrence matrix of Gabor filters responses. Furthermore, the second-order statistics of these co-occurrence matrices are computed to represent images' texture. T...Continue Reading

Citations

Jul 3, 2020·Journal of Cancer Research and Clinical Oncology·Peng JinYantao Tian
Oct 18, 2018·Journal of Medical Systems·Dingyun LiuTao Gan
Oct 8, 2020·World Journal of Gastroenterology : WJG·Peng-Hui NiuYing-Tai Chen
Oct 9, 2019·Gastroenterology·Catherine Le BerreLaurent Peyrin-Biroulet
May 11, 2021·World Journal of Gastroenterology : WJG·Jia-Sheng CaoXiu-Jun Cai
Jul 29, 2021·Gastroenterology Report·Daniela Cornelia LazărAdrian Goldiş

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