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.
Bilodeau
Guillaume-Alexandre
GA
Ecole Polytechnique de Montréal, C.P.6079, Succ. Centre-ville, Montréal, Que., Canada H3C 3A7. guillaume-alexandre.bilodeau@polymtl.ca
Shu
Yueyun
Y
Cheriet
Farida
F
D000465:Algorithms; D017586:Diskectomy / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional / Q000379:methods*; D020775:Thoracic Surgery, Video-Assisted / Q000379:methods; D013906:Thoracoscopy / Q000379:methods*