Lesion Age

Lesion age determination and segmentation are crucial for accurate diagnosis and treatment planning across various medical imaging applications, impacting patient care and clinical decision-making. Current research focuses on improving the accuracy and efficiency of lesion detection and characterization, particularly for small lesions, using advanced deep learning architectures like transformers and incorporating novel labeling strategies to enhance model performance. These advancements leverage techniques such as multi-task learning, uncertainty quantification, and improved registration methods to achieve more precise and reliable results, ultimately leading to better diagnostic tools and potentially reducing unnecessary procedures.