Robust Influence-based Training Methods for Noisy Brain MRI

arXiv:2403.10698v1 Announce Type: new
Abstract: Correctly classifying brain tumors is imperative to the prompt and accurate treatment of a patient. While several classification algorithms based on classical image processing or deep learning methods have been proposed to rapidly classify tumors in MR images, most assume the unrealistic setting of noise-free training data. In this work, we study a difficult but realistic setting of training a deep learning model on noisy MR images to classify brain tumors. We propose two training …

abstract algorithms arxiv brain classification cs.ai cs.cv data deep learning free image image processing images influence mri noise patient processing prompt robust the prompt training training data treatment tumors type