Anatomical Structure

Anatomical structure research focuses on accurately identifying, segmenting, and modeling anatomical features from medical images, aiming to improve diagnostic accuracy and treatment planning. Current research heavily utilizes deep learning, employing architectures like UNet, nnU-Net, Swin Transformers, and Generative Adversarial Networks (GANs) to achieve robust and efficient segmentation and synthesis of anatomical structures across various modalities (MRI, CT, ultrasound, PET). This work is significant for advancing medical image analysis, enabling more precise diagnoses, personalized treatment strategies, and improved understanding of anatomical variations in health and disease. Furthermore, these advancements are impacting fields beyond medicine, such as wood species identification and robotic surgery planning.