Deep Learning Based Interpretable Pediatric Brain Tumors Segmentation and Classification

The project project seeks to address key challenges in pediatric brain tumor imaging by creating a novel, interpretable deep learning framework that integrates tumor segmentation and classification. By leveraging interdisciplinary collaboration between AI scientists and healthcare professionals, this project aims to improve diagnosis, treatment planning, and patient outcomes for Pediatric Brain Tumors. The project will collect and process a comprehensive PBT MRI dataset, develop an explainable AI model using cutting-edge DL techniques, and validate its clinical application, ensuring transparency and trust in AI-driven clinical decision support systems.