Tissue Classification

Tissue classification, the automated identification of different tissue types in medical images, aims to improve diagnostic accuracy and efficiency across various medical specialties. Current research focuses on developing and refining deep learning models, such as U-Nets and Vision Transformers, often incorporating techniques like self-attention mechanisms and transfer learning to address challenges posed by limited annotated data and diverse imaging modalities. These advancements hold significant promise for accelerating diagnosis, enabling quantitative biomarker evaluation, and improving the precision of medical procedures like laser surgery and needle insertion. The ultimate goal is to augment pathologist workflows and enhance patient care through more objective and efficient tissue analysis.

Papers