Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering
Walid Obaid
Ajman University
Computer Science & IT Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : International Journal of Electrical and Computer Engineering

 1 
Mesenteric cyst detection and segmentation by multiple K-means clustering and iterative Gaussian filtering Mohamed Nasor; Walid Obaid
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4932-4941

Abstract

In this article a fully automated machine-vision technique for the detection and segmentation of mesenteric cysts in computed tomography (CT) images of the abdominal space is presented. The proposed technique involves clustering, filtering, morphological operations and evaluation processes to detect and segment mesenteric cysts in the abdomen regardless of their texture variation and location with respect to other surrounding abdominal organs. The technique is comprised of various processing phases, which include K-means clustering, iterative Gaussian filtering, and an evaluation of the segmented regions using area-normalized histograms and Euclidean distances. The technique was tested using 65 different abdominal CT scan images. The results showed that the technique was able to detect and segment mesenteric cysts and achieved 99.31%, 98.44%, 99.84%, 98.86% and 99.63% for precision, recall, specificity, dice score coefficient and accuracy respectively as quantitative performance measures which indicate very high segmentation accuracy.
Co-Authors Mohamed Nasor