Objective. To explore an inpainting method that can balance texture details and visual observability to eliminate the specular reflection (SR) regions in the colposcopic image, thus improving the accuracy of clinical diagnosis for cervical cancer. Methods. (1) To ensure smoothness, Gaussian Blur and filling methods are applied to the global image. (2) Striving to preserve the anatomical texture details of the colposcopic image as much as possible, the exemplar-based method is applied to local blocks. (3) The colposcopic images inpainted in the previous two steps are integrated, so that important information of non-SR regions is preserved based on eliminating SR regions. Results. In the subjective visual assessment of inpainting results, the average of 3.55 ranks first in the five comparison sets. As to the clinical test, comparing the diagnosis results of 6 physicians before and after eliminating SR regions, the average accuracy of two kinds of classifications increased by 1.44% and 2.03%, respectively. Conclusions. This method can effectively eliminate the SR regions in the colposcopy image and present a satisfactory visual effect. Significance. As a preprocessing method for computer-aided diagnosis systems, it can also improve physicians’ accuracy in clinical diagnosis.
Elimination of specular reflection and identification of ROI: The first step in automated detection of Cervical Cancer using Digital Colposcopy