Multiple Instance Learning for Glioma Diagnosis using Hematoxylin and Eosin Whole Slide Images: An Indian cohort Study

arXiv:2402.15832v1 Announce Type: new
Abstract: Brain tumors represent a severe and life-threatening condition, demanding precise diagnosis and tailored treatment strategies. This study advances patient care with findings from rigorous multiple-instance-learning experimentations across various feature extractors and aggregators in brain tumor histopathology. It establishes new performance benchmarks in glioma subtype classification across multiple datasets, including a novel dataset focused on the Indian demographic (IPD-Brain), providing a valuable resource for existing research. Using a ResNet-50, pretrained on histopathology datasets, for feature extraction, …

abstract advances arxiv brain cs.ai cs.cv diagnosis feature images indian instance life multiple patient patient care strategies study treatment tumors type