Gastrointestinal Tract

Research on the gastrointestinal (GI) tract focuses on improving diagnosis and treatment of GI diseases, particularly cancers, through advanced imaging analysis and AI-driven solutions. Current efforts leverage deep learning architectures like U-Net, Vision Transformers, and various CNNs, often incorporating techniques such as knowledge distillation and cost-sensitive learning to enhance accuracy and efficiency in tasks such as image segmentation, classification, and polyp detection. These advancements aim to automate time-consuming processes like organ segmentation for radiotherapy planning and improve the speed and accuracy of diagnoses from endoscopic images and biopsies, ultimately leading to better patient outcomes. The development of large, annotated datasets is also crucial to support the training and validation of these AI models.