Detection and correction of specular reflections for automatic surgical tool segmentation in thoracoscopic images

Abstract

This paper presents an algorithm that automatically detects and corrects specular reflections in thoracoscopic images and its application in the context of automatic segmentation of surgical tools. The detection is done by isolating the spike component of the specular reflection which is characterized by a bump at the end of the histogram of thoracoscopic images. The specular lobe is then extracted in the neighborhood of the spike component of the reflection. The result is a mask of the reflections positions in the image. Thereafter, the image is corrected using Oliveira et al.’s digital inpainting method. The automatic segmentation of surgical tools using the corrected images is then demonstrated. Results of the segmentation with and without the specular reflection elimination technique are compared. Moreover, 108 images extracted from 5 different surgeries performed under various conditions were considered to demonstrate the effectiveness of the proposed technique.