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Reseach Article

A Novel 3D-Overlap Metric for Medical Volume Images

by Badera Abu-Rumman, Zainab Al-Rahamneh, Asma’a Khtoom, Mohammad Ryalat
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 7
Year of Publication: 2024
Authors: Badera Abu-Rumman, Zainab Al-Rahamneh, Asma’a Khtoom, Mohammad Ryalat

Badera Abu-Rumman, Zainab Al-Rahamneh, Asma’a Khtoom, Mohammad Ryalat . A Novel 3D-Overlap Metric for Medical Volume Images. International Journal of Computer Applications. 186, 7 ( Feb 2024), 18-24. DOI=10.5120/ijca2024923403

@article{ 10.5120/ijca2024923403,
author = { Badera Abu-Rumman, Zainab Al-Rahamneh, Asma’a Khtoom, Mohammad Ryalat },
title = { A Novel 3D-Overlap Metric for Medical Volume Images },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2024 },
volume = { 186 },
number = { 7 },
month = { Feb },
year = { 2024 },
issn = { 0975-8887 },
pages = { 18-24 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2024923403 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-22T22:17:52.854045+05:30
%A Badera Abu-Rumman
%A Zainab Al-Rahamneh
%A Asma’a Khtoom
%A Mohammad Ryalat
%T A Novel 3D-Overlap Metric for Medical Volume Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 7
%P 18-24
%D 2024
%I Foundation of Computer Science (FCS), NY, USA

It is customary to measure the correctness of 3D medical segmentation of images and registration. As a result, the effectiveness and dependability of the used overlap metric are crucial to the evaluation process. A novel 3D-overlap metric for medical volume imaging is presented in this research. The proposed metric is specifically created to be orientated for medical volume images, unlike the present overlap metrics used in biomedical domains, which were primarily built for computer graphics applications. The peoposed complementary overlap metric furnishes statistically robust data, enabling visualization and analysis of the scale and localization of matching and mismatching volumes in addition to the merit number of the fraction of the region match. This metric is practical for medical images since it provides particular values for the axial, sagittal, and coronal planes. To guarantee reliability and generalizability in this work, six distinct datasets were employed for comprehensive assessment. To assess the proposed metric, two methods were employed. The first step is to look at the association between the proposed overlap metric and other, more commonly used and recognized overlap metrics. The second involves examining the results of the proposed metric for specific test instances where we are aware of the expected trend of the right outputs in advance. The findings demonstrate the value of applying the proposed overlap metric to assess how well medical image segmentation and registration performed.

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Index Terms

Computer Science
Information Sciences
Image Segmentation
Medical Images
Biomedical Engineering.


Overlap Metric Segmentation 3-D Medical Images Axial Sagittal Coronal Volume of Match.