Segmenting skin ulcers and measuring the wound area using deep convolutional networks.
Journal:
Computer methods and programs in biomedicine
Published Date:
Jul 1, 2020
Abstract
BACKGROUND AND OBJECTIVES: Bedridden patients presenting chronic skin ulcers often need to be examined at home. Healthcare professionals follow the evolution of the patients' condition by regularly taking pictures of the wounds, as different aspects of the wound can indicate the healing stages of the ulcer, including depth, location, and size. The manual measurement of the wounds' size is often inaccurate, time-consuming, and can also cause discomfort to the patient. In this work, we propose the Automatic Skin Ulcer Region Assessment ASURA framework to accurately segment the wound and automatically measure its size.