3D Lesion

3D lesion analysis focuses on accurately identifying, segmenting, and characterizing three-dimensional lesions from medical images, primarily computed tomography (CT) scans, to improve diagnostic accuracy and treatment planning. Current research emphasizes developing robust deep learning models, including transformer-based networks and graph neural networks, to address challenges such as inter-observer variability in lesion assessment and the need for efficient, universal lesion segmentation across diverse anatomical locations. These advancements are crucial for improving the speed and accuracy of radiological workflows, enabling more precise quantitative analysis of lesion growth kinetics, and ultimately leading to better patient care.