Fully automatic anatomical, pathological, and functional segmentation from CT scans for hepatic surgery
Journal of Computer-Aided Surgery
Objective: To improve the planning of hepatic surgery, we have developed a fully automatic anatomical, pathological and functional segmentation of the liver derived from a spiral CT scan. Materials and methods : From a 2mm thick enhanced spiral CT scan, a first stage automatically delineates skin, bones, lungs, kidneys and spleen, by combining the use of thresholding, mathematical morphology and distance maps. Next, a reference 3D model is immerged in the image and automatically deformed to
... r contours. Then an automatic gaussians fitting on the imaging histogram estimates the intensities of parenchyma, vessels and lesions. This first result is next improved through an original topological and geometrical analysis, providing an automatic delineation of lesions and veins. Finally, a topological and geometrical analysis based on medical knowledge provides hepatic functional information invisible in medical imaging: portal vein labeling and hepatic anatomical segmentation according to the Couinaud classification. Results: Clinical validation performed on more than 30 patients shows that this method's delineation of anatomical structures is often more sensitive and more specific than manual delineation by a radiologist. Conclusion: This study describes the methodology used to create the automatic segmentation of the liver with delineation of important anatomical, pathological and functional structures from a routine CT scan. Using the methods proposed in this study, we have confirmed the accuracy and utility of the creation of 3 -dimensional liver model when compared with the conventional reading of the CT scan by a radiologist. This work, may allow an improvement in preoperative planning of hepatic surgery by more p recisely delineating liver pathology and its relation to normal hepatic structures. In the future this data may be integrated with computer-assisted surgery and thus represents a first step towards the development of an augmented reality surgical system.