Segmentation and Feature Extraction of Endoscopic Images for Making Diagnosis of Acute Appendicitis
- 作者: Ye S.1, Nedzvedz A.2,3, Ye F.1, Ablameyko S.2,3
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隶属关系:
- Zhejiang Shuren University
- Belarusian State University
- United Institute of Informatics Problems of National Academy of Sciences
- 期: 卷 29, 编号 4 (2019)
- 页面: 738-749
- 栏目: Applied Problems
- URL: https://bakhtiniada.ru/1054-6618/article/view/195761
- DOI: https://doi.org/10.1134/S1054661819040205
- ID: 195761
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详细
In recent years, digital endoscopy has established as key technology for medical screenings and minimally invasive surgery. Endoscopy image processing techniques have been applied to the diagnosis of diseases. In this paper, an effective approach is proposed to process endoscopic images to detect acute appendicitis. For this purpose, we first introduced image enhancement techniques that allow us to improve quality of endoscopic image for further processing. A simple and effective image segmentation technique was developed to detect vessels and vermiform appendix. The hierarchical set of features have been extracted for detecting acute appendicitis. It includes geometrical, colorimetric, densitometric, and topological features. For each appendicitis feature discriminant indexes have been introduced for diagnosis. This method has achieved good results in clinical application.
作者简介
Shiping Ye
Zhejiang Shuren University
编辑信件的主要联系方式.
Email: zjsruysp@163.com
中国, Hangzhou, 310015
A. Nedzvedz
Belarusian State University; United Institute of Informatics Problems of National Academy of Sciences
编辑信件的主要联系方式.
Email: nedzveda@tut.by
白俄罗斯, Minsk, 220030; Minsk, 220020
Fangfang Ye
Zhejiang Shuren University
编辑信件的主要联系方式.
Email: cliney@zju.edu.cn
中国, Hangzhou, 310015
S. Ablameyko
Belarusian State University; United Institute of Informatics Problems of National Academy of Sciences
编辑信件的主要联系方式.
Email: ablameyko@bsu.by
白俄罗斯, Minsk, 220030; Minsk, 220020
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