3D Medical Imaging

3D medical imaging research focuses on developing and improving methods for analyzing three-dimensional medical scans (e.g., CT, MRI) to aid in diagnosis and treatment planning. Current research emphasizes leveraging deep learning models, particularly transformer-based architectures and 3D convolutional neural networks, to perform tasks such as segmentation, detection, and report generation. A significant challenge is the need for large, annotated datasets, leading to exploration of techniques like active learning, self-supervised pre-training, and data augmentation to overcome data scarcity. These advancements hold significant promise for improving diagnostic accuracy, streamlining workflows, and ultimately enhancing patient care.