Open AccessAutomatic segmentation of large bowl obstruction area with hough transform from erect abdominal radiograph images
Author(s) -
Kwang-Baek Kim,
Doo Heon Song,
Young Woon Woo
Publication year - 2021
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijece.v11i3.pp2674-2679
Subject(s) - hough transform , artificial intelligence , computer science , computer vision , bowel obstruction , segmentation , feature (linguistics) , radiography , medicine , radiology , image (mathematics) , linguistics , philosophy
Large bowel obstruction is less frewuent but often appears acute and needs emergent treatment. Erect abdominal radiograph is usually the first imaging study performed in patients suspected of having large bowel obstruction. However, that mordality suffers from operator subjectivity thus a fully automatic computer aied tool is necessary. In this paper, we peopose an automatic large bowel feature (air-fluid region) segmentation method based on Canny edge detection and Hough transform. In experiment, the proposed method was successful in finding target region from large bowel obstruction patients’ radiographic images in all 30 cases provided. Whilie limited only applicable to the large bowel obstruction cases, the proposed method is practically feasible in application.