Accurate Segmentation of Pigmented Skin Lesions Using Grounded-segment-anything

Takashi Nagaoka Melanoma is a highly aggressive form of skin cancer, and accurately segmenting pigmented lesions is crucial for early diagnosis. However, manual annotation is time-consuming, subjective, and requires expertise from dermatologists. To address these challenges, we propose a fully unsupervised segmentation approach using grounded-segment-anything model (Grounded-SAM), which operates without the need for annotated training data.