Multistage graph-based segmentation of thoracoscopic images

This paper presents a graph-based segmentation method using multiple criteria in successive stages to segment thoracoscopic images acquired during a diskectomy procedure commonly used for thoracoscopic anterior release and fusion for scoliosis treatment. Starting with image pre-processing, including Gaussian smoothing, brightness and contrast enhancement, and histogram thresholding, a standard graph-based method is applied to produce a coarse segmentation of thoracoscopic images. Next, regions are further merged in a multistage graph-based process based on features like grey-level similarity, region size and common edge length. Experimental results show that our approach achieves good spatial coherence, accurate edge location and appropriate segmentation of the regions of interest from a sequence of thoracoscopic images.