CBTN Connect Dipgr Asnr Miccai

CBTN Connect Dipgr Asnr Miccai encompasses a series of challenges focused on advancing medical image analysis, particularly in the segmentation and detection of anatomical structures and pathologies. Current research emphasizes improving the accuracy and robustness of deep learning models, such as U-Net variations and ensemble methods, for tasks ranging from brain tumor segmentation in pediatrics to aortic vessel and dental structure identification. These efforts aim to improve diagnostic accuracy, aid in surgical planning, and ultimately enhance patient care by providing more efficient and objective tools for clinicians. A key challenge remains addressing performance variability and ensuring reliable generalization across diverse datasets and clinical settings.