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Journal of Biomed Research

ISSN: 2693-5910

Commentary Open Access
Volume 5 | Issue 1 | DOI: https://doi.org/10.46439/biomedres.5.051

Recent advances and challenges in brain tumor segmentation utilizing α-expansion graph cut

Roaa Soloh1,*, Hassan Alabboud2, Ahmad Shahin3,4, Adnan Yassine5,6, Abdallah El Chakik7
  • 1Computer & Information Systems Department, Rafik Hariri University, Mechref, Lebanon
  • 2Faculty of Economics & Business Administration, Lebanese University, Lebanon
  • 3LIA Laboratory, Doctoral School of Sciences & Technology Lebanese University, Lebanon
  • 4Department of Computer Information Systems, Lebanese University, Lebanon
  • 5UNIHAVRE, LMAH, FR-CNRS-3335, ISCN, Normandie Universit., Le Havre, France
  • 6UNILEHAVRE, Institut Suprieur d’Etudes Logistiques (ISEL), Normandie Universit., Le Havre, France
  • 7Department of Computer Science, Beirut Arab University, Tripoli, Lebanon
+ Affiliations - Affiliations

Corresponding Author

Roaa Soloh, solohrk@rhu.edu.lb

Received Date: July 29, 2024

Accepted Date: September 16, 2024

Citation:

Soloh R, Alabboud H, Shahin A, Yassine A, Chakik A E . Recent advances and challenges in brain tumor segmentation utilizing α-expansion graph cut. J Biomed Res. 2024;5(1):115-118.


Copyright: © 2024 Soloh R, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

This commentary summarizes our team's recent study, "Brain Tumor Segmentation Based on α-Expansion Graph Cut," by discussing the recent advances in deep learning integration, multimodality imaging, and real-time segmentation tools. It also highlights the strengths of the method in energy minimization and noise handling done throughout the study, while it addresses the challenges related to scalability, deep learning integration, and generalization. This brief overview provides insights into current advances and future directions in brain tumor segmentation.

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