Explainability of deep neural networks for MRI analysis of brain tumors

1

Brain tumors, including glioblastoma, are a leading cause of cancer death in adults, complicating treatment due to difficulty in localization.
2

MRI provides critical imaging for brain tumor detection, but interpreting multi-parametric images is challenging for physicians.
3

Computer-aided diagnosis systems enhance tumor detection and analysis, leveraging deep learning for improved segmentation and classification.
4

Explainable AI (XAI) is essential in medical imaging to ensure transparency in deep learning models, fostering trust among clinicians.
5

The proposed NeuroXAI framework aims to provide interpretable sensitivity maps for 2D and 3D brain imaging without compromising model performance.

International Journal Of Computer Assisted Radiology And Surgery

by Ramy A. Zeineldin, Mohamed E. Karar, Ziad Elshaer, ·Jan Coburger, Christian R. Wirtz, Oliver Burgert, Franziska Mathis-Ullrich
April 23, 2022

1