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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 4, 2025.
Abstract: Image segmentation is an important aspect of image processing and analysis. Medical imaging segmentation is critical for providing noninvasive information about human body structure that helps physicians analyze body anatomies efficiently. Until recently, various medical imaging segmentation approaches have been presented; however, these approaches are deficient in segmenting abdominal organs due to the significant similarity in their intensity levels. The purpose of this research is to propose a method to facilitate the segmentation of abdominal organs and improve the performance of the segmentation. The core functionality of this research is based on the extraction of rib bone from muscle tissues prior to the application of segmentation. This way, efficient segmentation of abdominal organs can be achieved by isolating the rib bone from the muscle tissues located between the rib bone. The proposed rib bone extraction mechanism is applied to four slices of the MICCAI2007 liver data set to isolate muscle tissues from liver tissues that have significant intensity similarity to liver tissues. The results indicate that the proposed extraction of rib bone efficiently isolated muscle tissues from linked liver tissues and improved the segmentation performance.
Mahmoud S. Jawarneh, Shahid Munir Shah, Mahmoud M. Aljawarneh, Ra’ed M. Al-Khatib and Mahmood G. Al-Bashayreh, “Rib Bone Extraction Towards Liver Isolating in CT Scans Using Active Contour Segmentation Methods” International Journal of Advanced Computer Science and Applications(IJACSA), 16(4), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160497
@article{Jawarneh2025,
title = {Rib Bone Extraction Towards Liver Isolating in CT Scans Using Active Contour Segmentation Methods},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160497},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160497},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {4},
author = {Mahmoud S. Jawarneh and Shahid Munir Shah and Mahmoud M. Aljawarneh and Ra’ed M. Al-Khatib and Mahmood G. Al-Bashayreh}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.