LIver Lesion

Liver lesion detection and segmentation are crucial for early diagnosis and treatment of liver diseases, particularly cancer. Current research focuses on improving the accuracy and robustness of automated methods using deep learning architectures like UNet and transformers, often incorporating multi-phase CT or MRI data and employing techniques such as contrastive learning and attention mechanisms to address the heterogeneity and variability of lesions. These advancements aim to assist radiologists by improving diagnostic accuracy, reducing false positives, and ultimately enhancing patient care through faster and more reliable diagnoses.