Detection of infected wounds in abdominal surgery images using fuzzy logic and fuzzy sets

Patients undergoing abdominal operations should perform a postoperative follow-up. The subsequent face-to-face consultations have an economic cost to the health system and can affect the quality of life of patients. The follow-up of the patients could be simplified using a smartphone application that, based on an image of the surgical wound and a simple questionnaire, could detect postoperative complications. One of the main complications is the appearance of infection in the wound, signaled by the redness that appears around the wound and the staples. In this paper we present a method to automatically detect infection in surgical wounds. The method has been divided into three steps. First step in this process is to locate and remove the staples that keep the wound closed because they distort the overall color of the image. To do this, after transforming the image to the HSV color space, we apply the Sobel gradient in the vertical direction of the V channel. The discrete fuzzy mathematical morphology process it to yield a binary mask with areas indicating the position of the staples. Second, using a fuzzy mathematical morphology for images in the CIELab color space, we apply an inpainting algorithm to restore the regions detected as staples. Third, using triangular and trapezoidal fuzzy sets, we determine if there are areas of the wound that present a deviation to the red color. Our experiments show that the proposed method can be successfully used to detect the possibility of infection in the wound. In addition, the algorithms have been designed using simple operations so that the method could be introduced in a smartphone application.