Brain Tumor
Brain tumor research focuses on improving the accuracy and efficiency of diagnosis and treatment planning, primarily using magnetic resonance imaging (MRI). Current research emphasizes the development of sophisticated deep learning models, including convolutional neural networks (CNNs), vision transformers, and hybrid architectures incorporating attention mechanisms, to analyze multi-modal MRI data and perform tasks such as tumor segmentation and classification. These advancements aim to improve diagnostic accuracy, personalize treatment strategies, and ultimately enhance patient outcomes, impacting both clinical practice and the broader medical imaging field.
Papers
Parameter-efficient Fine-tuning for improved Convolutional Baseline for Brain Tumor Segmentation in Sub-Saharan Africa Adult Glioma Dataset
Bijay Adhikari, Pratibha Kulung, Jakesh Bohaju, Laxmi Kanta Poudel, Confidence Raymond, Dong Zhang, Udunna C Anazodo, Bishesh Khanal, Mahesh Shakya
Spatial Brain Tumor Concentration Estimation for Individualized Radiotherapy Planning
Jonas Weidner, Michal Balcerak, Ivan Ezhov, André Datchev, Laurin Lux, Lucas Zimmerand Daniel Rueckert, Björn Menze, Benedikt Wiestler