A Transformer-Based CBIR System for Cutaneous Ulcer Analysis with LLM Assistance - dos Santos, Gabriel B.; Jorge, Ana Elisa; Traina, Agma J. M.; Cazzolato, Mirela T. (Anais Estendidos do Simpósio Brasileiro de Banco de Dados (SBBD), 2026)
Chronic dermatological ulcers are a public health concern, with clinical assessment subject to inter-observer variability. Content-Based Image Retrieval (CBIR) systems offer decision support, yet Transformer-based feature extractors remain underexplored in this domain. This work presents a CBIR system augmented with a Large Language Model (LLM) layer that summarizes retrieved cases in natural clinical language. To inform its configuration, we compare five Transformer extractors against handcrafted descriptors and a random reference on a dataset labeled by tissue composition, using Precision@K, MAP, macro-mAP, and NDCG@K with graded Jaccard relevance. The study identifies a configuration with consistent performance across all metrics.