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
Adaptive PromptNet For Auxiliary Glioma Diagnosis without Contrast-Enhanced MRI
Yeqi Wang, Weijian Huang, Cheng Li, Xiawu Zheng, Yusong Lin, Shanshan Wang
Brain Tumor Sequence Registration with Non-iterative Coarse-to-fine Networks and Dual Deep Supervision
Mingyuan Meng, Lei Bi, Dagan Feng, Jinman Kim