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Found 5 papers, 2 papers with code
Multi-modal Wound Classification using Wound Image and Location by Deep Neural Network
This study developed a deep neural network-based multi-modal classifier using wound images and their corresponding locations to categorize wound images into multiple classes, including diabetic, pressure, surgical, and venous ulcers.
Multiclass Burn Wound Image Classification Using Deep Convolutional Neural Networks
A pre-trained deep convolutional neural network, AlexNet, is fine-tuned using a burn wound image dataset and utilized as the classifier.
Multiclass Wound Image Classification using an Ensemble Deep CNN-based Classifier
Acute and chronic wounds are a challenge to healthcare systems around the world and affect many people's lives annually.
Fully Automatic Wound Segmentation with Deep Convolutional Neural Networks
Fully automatic segmentation of wound areas in natural images is an important part of the diagnosis and care protocol since it is crucial to measure the area of the wound and provide quantitative parameters in the treatment.
Image Based Artificial Intelligence in Wound Assessment: A Systematic Review
Efficient and effective assessment of acute and chronic wounds can help wound care teams in clinical practice to greatly improve wound diagnosis, optimize treatment plans, ease the workload and achieve health related quality of life to the patient population.
