Diabetic foot ulcers (DFU) are one of the serious complications of diabetes that can lead to amputations and high healthcare costs. Regular monitoring and early diagnosis are critical for reducing the clinical burden and the risk of amputation. The aim of this study is to investigate the impact of using multimodal images on deep learning models for the classification of DFU stages. To this end, we developed a Raspberry Pi-based portable imaging system capable of simultaneously capturing RGB and thermal images. Using this prototype, a dataset consisting of 1,205 samples was collected in a hospital setting. The dataset was labeled by experts into six distinct stages. To evaluate the models performance, we prepared three different training sets: RGB-only, thermal-only, and RGB+Thermal (with the thermal image added as a fourth channel). We trained these training sets on the DenseNet121, EfficientNetV2, InceptionV3, ResNet50, and VGG16 models. The results show that the multimodal training dataset, in which RGB and thermal data are combined across four channels, outperforms single-modal approaches. The highest performance was observed in the VGG16 model trained on the RGB+Thermal dataset. The model achieved an accuracy of 93.25%, an F1-score of 92.53%, and an MCC of 91.03%. Grad-CAM heatmap visualizations demonstrated that the thermal channel helped the model focus on the correct location by highlighting temperature anomalies in the ulcer region, while the RGB channel supported the decision-making process with complementary structural and textural information.
A Cloud-based Deep Learning Framework for Remote Detection of Diabetic Foot Ulcers
Manchester Metropolitan University（曼彻斯特城市大学）；Lancashire Teaching Hospitals NHS Foundation Trust（兰开夏教学医院NHS基金会信托）；The University of Manchester（曼彻斯特大学）；Manchester University NHS Foundation Trust（曼彻斯特大学NHS基金会信托）；Salford Royal NHS Foundation Trust（索尔福德皇家NHS基金会信托）
Diabetic Foot Ulcer Grand Challenge 2021: Evaluation and Summary
Manchester Metropolitan University（曼彻斯特城市大学）；Lancashire Teaching Hospitals NHS Foundation Trust（兰开夏教学医院NHS基金会信托）；Waikato District Health Board（怀卡托地区卫生局）；University of Southern California（南加利福尼亚大学）
Manchester Metropolitan University（曼彻斯特城市大学）；Lancashire Teaching Hospitals NHS Foundation Trust（兰开夏教学医院NHS基金会信托）；Waikato District Health Board（怀卡托地区卫生委员会）
Boosting EfficientNets Ensemble Performance via Pseudo-Labels and Synthetic Images by pix2pixHD for Infection and Ischaemia Classification in Diabetic Foot Ulcers
University of Applied Sciences and Arts Dortmund (FH Dortmund)（多特蒙德应用科学与艺术大学）；University Hospital Essen（埃森大学医院）
Domain-Specific Deep Learning Feature Extractor for Diabetic Foot Ulcer Detection
Institute of Biomedical Engineering, University of Toronto（多伦多大学生物医学工程研究所）；KITE, Toronto Rehabilitation Institute, University Health Network（大学健康网络多伦多康复研究所KITE部门）
DFUNet: Convolutional Neural Networks for Diabetic Foot Ulcer Classification
Manchester Metropolitan University（曼彻斯特城市大学）；University of Manchester（曼彻斯特大学）；Lancashire Teaching Hospital（兰开夏教学医院）；Lancashire Care NHS Foundation Trust（兰开夏护理NHS基金会信托）
Translating Clinical Delineation of Diabetic Foot Ulcers into Machine Interpretable Segmentation
Manchester Metropolitan University（曼彻斯特城市大学）；Lancashire Teaching Hospitals NHS Foundation Trust（兰开夏教学医院NHS基金会信托）；Waikato District Health Board（怀卡托地区卫生委员会）；United Lincolnshire Hospitals NHS Trust（联合林肯郡医院NHS信托）；Jersey General Hospital（泽西总医院）；Eastbourne District General Hospital（伊斯特本地区综合医院）
A quantitative comparison of plantar soft tissue strainability distribution and homogeneity between ulcerated and non-ulcerated patients using strain elastography
Staffordshire University（斯塔福德郡大学）；AR Diabetes Hospitals（AR糖尿病医院）；Technische Universität München（慕尼黑工业大学）
UlcerGPT: A Multimodal Approach Leveraging Large Language and Vision Models for Diabetic Foot Ulcer Image Transcription
KITE Research Institute（凯特研究所）；University Health Network（大学健康网络）；Institute of Biomedical Engineering, University of Toronto（多伦多大学生物医学工程研究所）；University of Toronto Mississauga（多伦多大学密西沙加分校）
Analysis Towards Classification of Infection and Ischaemia of Diabetic Foot Ulcers
Faculty of Science and Engineering, Manchester Metropolitan University（曼彻斯特城市大学科学与工程学院）；Lanchashire Teaching Hospitals（兰开夏教学医院）；Waikato District Health Board（怀卡托地区卫生局）
DFUC2020: Analysis Towards Diabetic Foot Ulcer Detection
Manchester Metropolitan University（曼彻斯特城市大学）；Lancashire Teaching Hospital（兰开夏教学医院）；Waikato District Health Board（怀卡托地区卫生委员会）；Manipal College of Health Professions（马尼帕尔健康专业学院）；University of Waikato（怀卡托大学）；University of Manchester（曼彻斯特大学）；University of Southern California（南加州大学）；Baylor College of Medicine（贝勒医学院）
Deep Learning in Diabetic Foot Ulcers Detection: A Comprehensive Evaluation
Manchester Metropolitan University（曼彻斯特城市大学）；Keio University（庆应义塾大学）；Baker Heart and Diabetes Institute（贝克心脏与糖尿病研究所）；University of Applied Sciences and Arts Dortmund (FH Dortmund)（多特蒙德应用科学与艺术大学）；Dartmouth College（达特茅斯学院）；Shanghai University（上海大学）
ConMatFormer: A Multi-attention and Transformer Integrated ConvNext based Deep Learning Model for Enhanced Diabetic Foot Ulcer Classification
Department of Information Technology（信息科技系）；Charles Darwin University（查尔斯·达尔文大学）；Department of Computer Science and Engineering（计算机科学与工程系）；University of Liberal Arts Bangladesh（孟加拉自由大学）；BRAC University（BRAC大学）；Center for Advanced Analytics (CAA), COE for Artificial Intelligence, Faculty of Engineering & Technology (FET)（高级分析中心（CAA）、人工智能学院、工程与技术学院）；Multimedia University Melaka（马六甲多媒体大学）；American International University-Bangladesh（美国国际大学-孟加拉）
Recognition of Ischaemia and Infection in Diabetic Foot Ulcers: Dataset and Techniques
Manchester Metropolitan University（曼彻斯特城市大学）；Lancashire Teaching Hospital（兰开夏教学医院）；University of Manchester（曼彻斯特大学）；Manchester Royal Infirmary（曼彻斯特皇家医院）；Sun Yat-sen University（中山大学）
Synthesizing Diabetic Foot Ulcer Images with Diffusion Model
Institute of Biomedical Engineering, University of Toronto（多伦多大学生物医学工程研究所）；University Health Network（多伦多大学健康网络）；Zivot Limb Preservation Centre, Peter Lougheed Centre（齐沃特肢体保护中心（彼得·劳埃德中心））；Cumming School of Medicine, University of Calgary（卡尔加里大学卡明医学院）
Federated Uncertainty-Aware Aggregation for Fundus Diabetic Retinopathy Staging
Institute of High Performance Computing (IHPC)（高性能计算研究所）；Agency for Science, Technology and Research (A*STAR)（科技研究局）；College of Computer Science and Technology（计算机科学与技术学院）；Nanjing University of Aeronautics and Astronautics（南京航空航天大学）；National Key Laboratory of Fundamental Science on Synthetic Vision（合成视觉基础科学国家重点实验室）；Sichuan University（四川大学）
DRStageNet: Deep Learning for Diabetic Retinopathy Staging from Fundus Images
Technion, Israel Institute of Technology（以色列理工学院）；Massachusetts Institute of Technology（麻省理工学院）；Beth Israel Deaconess Medical Center（贝斯以色列女执事医疗中心）；Harvard T.H. Chan School of Public Health（哈佛大学陈曾熙公共卫生学院）；São Paulo Federal University（圣保罗联邦大学）
WoundNet-Ensemble: A Novel IoMT System Integrating Self-Supervised Deep Learning and Multi-Model Fusion for Automated, High-Accuracy Wound Classification and Healing Progression Monitoring
The Catholic University of America（美国天主教大学）；Center for Advanced Research in Computer Engineering（计算机工程高级研究中心）
Fine-tuning Vision Language Models with Graph-based Knowledge for Explainable Medical Image Analysis
School of Electrical and Computer Engineering, Cornell University（电气与计算机工程学院，康奈尔大学）；School of Computation, Information and Technology, Technical University of Munich（计算、信息与技术学院，慕尼黑技术大学）；Cornell Tech（康奈尔科技）；Weill Cornell Medicine（韦尔·康奈尔医学）
Integrated Image and Location Analysis for Wound Classification: A Deep Learning Approach
University of Wisconsin-Milwaukee（威斯康星大学密尔沃基分校）；Advancing the Zenith of Healthcare (AZH) Wound and Vascular Center（医疗保健提升巅峰伤口与血管中心）；University of Wisconsin Milwaukee（威斯康星大学密尔沃基分校）
Integrating Vision and Location with Transformers: A Multimodal Deep Learning Framework for Medical Wound Analysis
University of Zanjan（赞詹大学）；Islamic Azad University Science and Research Branch（伊斯兰阿扎德大学科学与研究分支）；Samarkand State University named after Sharof Rashidov（沙罗夫·拉希多夫命名的撒马尔罕州立大学）；Kimyo International University In Tashkent（塔什干基莫国际大学）；University of Tehran（德黑兰大学）；Drexel University（德雷塞尔大学）
