Brain Lesion

Brain lesion segmentation, the automated identification and delineation of damaged brain tissue in medical images, is crucial for accurate diagnosis and treatment planning of neurological disorders. Current research focuses on improving the accuracy and robustness of deep learning models, particularly convolutional neural networks (CNNs) and transformers, often incorporating techniques like data augmentation, multi-modal fusion, and uncertainty quantification to address challenges such as limited annotated data and inter-scanner variability. These advancements aim to improve the efficiency and reliability of lesion detection across various imaging modalities and lesion types, ultimately leading to more precise diagnoses and personalized treatment strategies.