Open AccessA Novel Super Voxel-based 3D Segmentation Method for Irritable Bowel Syndrome
Author(s) -
Adithya Pothan Raj,
Mohan Kumar Pasupuleti
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.e1189.0585c19
Subject(s) - artificial intelligence , computer science , computer vision , segmentation , image segmentation , smoothing , scale space segmentation , rgb color model , pattern recognition (psychology) , feature (linguistics) , linguistics , philosophy
The main aim of this research paper is to implement a model-driven machine learning based adaptive 3D Segmentation Scheme for detecting the IBS (Irritable bowel syndrome) disease. This algorithm taking into account by endoscopy driven visual images for the purpose of machine analyzing and convert that 2D RGB coordinates into 3D RGB coordinates for improving the accuracy of the segmentation. In previous segmentation schemes, the IBS images are obtained by the use of ultrasound imaginary technique, but the main issue of the imaginary was the noise present in the images. We are overcoming this issue by applying the endoscopy images. Adaptive smoothing technique used in pre-processing stages with neighboring pixel reference. The feature data extraction stages estimate the shape and color and region-based features for segmentation. The proposed scheme performance with our 50 image Database shows that the results accuracy of proposed system outperforms multiple conventional segmentation methods