LAUSR

Wound care is a critical aspect of healthcare that involves treating and managing various types of wounds, typically caused by injuries, surgery, or chronic diseases such as diabetes. Chronic wounds can be particularly challenging to manage and often require 3 to 6 months of long-term care. In a few instances, healing durations are highly unpredictable and can vary depending on the severity of the wound, the patient’s overall health, and other factors such as medication, nutrition, age, comorbidity, environment, etiology, and immune system function. A chronic wound can significantly impact the quality of life, causing pain, discomfort, limited mobility, higher healthcare cost, and even mortality in severe cases. Effective wound care is crucial for promoting complete and timely healing and reducing the risk of complications that may lead to amputation, infection, and other potentially life-threatening outcomes. This work aims to develop a system that automizes to determine the wound boundaries leveraging the DeepLabV3+SE, measures the wound characteristics such as size and area, and wound shape using a pipeline of morphological operations and connected component analysis modules. The proposed system’s performance was evaluated using the publicly available dataset. Results demonstrate that the DeepLabV3+SE has outperformed with significantly high dice and IOU scores of 0.923 and 0.924, respectively, compared with several state-of-the-art methods.