TransUNet-GradCAM: A Hybrid Transformer-U-Net with Self-Attention and Explainable Visualizations for Foot Ulcer Segmentation

arXiv:2508.03758 · eess.IV, cs.CV · Submitted 2025-08-04 · Read on arXiv

eess.IV, cs.CV

Submitted: 2025-08-04

Updated: 2026-09-27

Code: https://github.com/FereshteShakeri/few-shot-MedVLMs

Terminology

• Transformer — 41× in this paper · explained in 2 episodes
• Ablation — 15× in this paper · explained in 1 episode
• Accuracy — 15× in this paper · explained in 1 episode
• Explainability — 15× in this paper · explained in 3 episodes
• Calibration — 12× in this paper · explained in 7 episodes
• AUC — 9× in this paper · explained in 2 episodes
• External Validation — 9× in this paper · explained in 2 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• Domain Shift — 8× in this paper · explained in 4 episodes
• Generalization — 7× in this paper · explained in 13 episodes
• Robustness — 7× in this paper · explained in 5 episodes
• Attention Mechanism — 5× in this paper · explained in 3 episodes
• Interpretability — 5× in this paper · explained in 15 episodes
• Dice Similarity Coefficient — 4× in this paper
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• U-net architecture — 4× in this paper · explained in 3 episodes
• Ablation study — 3× in this paper · explained in 1 episode
• Average Symmetric Surface Distance — 3× in this paper
• Expected Calibration Error — 3× in this paper
• Feature Extraction — 3× in this paper · explained in 2 episodes
• Advancing the Zenith of Healthcare — 2× in this paper
• Generalizability — 2× in this paper · explained in 6 episodes
• Transfer Learning — 2× in this paper · explained in 10 episodes
• Transferability — 2× in this paper · explained in 4 episodes
• Accountability — 1× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Edge Devices — 1× in this paper · explained in 2 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Institute of Electrical and Electronics Engineers — 1× in this paper
• International Conference on Computer Vision — 1× in this paper
• Loss Function — 1× in this paper · explained in 2 episodes
• Segmentation Masks — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Vision Transformer (ViT) — 1× in this paper · explained in 2 episodes
• Vision-language models — 1× in this paper · explained in 2 episodes
• Zero-Shot Transfer — 1× in this paper · explained in 4 episodes

Sources

• PerceptronCARE: A Deep Learning-Based Intelligent Teleophthalmology Application for Diabetic Retinopathy Diagnosis
• Understanding implementation pitfalls of distance-based metrics for image segmentation
• Do Diabetic Foot Ulcer Segmentation Models Generalize? A Cross-Dataset Benchmark of CNN and Transformer Architectures

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