An XAI-enhanced efficientNetB0 framework for precision brain tumor detection in MRI imaging.

Journal: Journal of neuroscience methods
Published Date: Jul 20, 2024

Abstract

BACKGROUND: Accurately diagnosing brain tumors from MRI scans is crucial for effective treatment planning. While traditional methods heavily rely on radiologist expertise, the integration of AI, particularly Convolutional Neural Networks (CNNs), has shown promise in improving accuracy. However, the lack of transparency in AI decision-making processes presents a challenge for clinical adoption.

Authors

  • Mahesh T R
    Department of Computer Science and Engineering, Faculty of Engineering and Technology, JAIN (Deemed-to-be University), 562112, Bangalore, India.
  • Muskan Gupta
    Department of Computer Science & Engineering, Faculty of Engineering and Technology, JAIN (Deemed-to-be University), Bengaluru, 562112, India.
  • Anupama T A
    Department of Computer Science and Engineering, Siddaganga Institute of Technology, Tumakuru 572103, India.
  • Vinoth Kumar V
    School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, India. Electronic address: vinothkumar.v@vit.ac.in.
  • Oana Geman
    Stefan Cel Mare University of Suceava Romania, Suceava, Romania.
  • Dhilip Kumar V
    Vel Tech Rangarajan Dr.Sagunthala R & D Instiute of Science and Technology, Chennai, India. Electronic address: vdhilipkumar@veltech.edu.in.

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