Abstract
Automated tracking of wound-healing progress using images from smartphones can be useful and convenient for the patient to perform at home. To evaluate the feasibility, 119 images were taken with an iPhone smartphone during the treatment of a chronic wound at one patient's home. An image analysis algorithm was developed to quantitatively classify wound content as an index of wound healing. The core of the algorithm involves transforming the colour image into hue-saturation-value colour space, after which a threshold can be reliably applied to produce segmentation using the Black-Yellow-Red wound model. Morphological transforms are used to refine the classification. This method was found to be accurate and robust with respect to lighting conditions for smartphone-captured photos. The wound composition percentage showed a different trend from the wound area measurements, suggesting its role as a complementary metric. Overall, smartphone photography and automated image analysis is a promising cost-effective way of monitoring patients. While the current setup limits our capability of measuring wound area, future smartphones equipped with depth-sensing technology will enable accurate volumetric evaluation in addition to composition analysis.