Liver vessels segmentation using a hybrid geometrical moments/graph cuts method.
This paper describes a fast and fully automatic method for liver vessel segmentation on computerized tomography scan preoperative images. The basis of this method is the introduction of a 3-D geometrical moment-based detector of cylindrical shapes within the minimum-cut/maximum-flow energy minimization framework. This method represents an original way to introduce a data term as a constraint into the widely used Boykov's graph cuts algorithm, and hence, to automate the segmentation. The method is evaluated and compared with others on a synthetic dataset. Finally, the relevancy of our method regarding the planning of a necessarily accurate percutaneous high-intensity focused ultrasound surgical operation is demonstrated with some examples.
Institut National de la Santé et de la Recherche Médicale (INSERM) U642, F-35000 Rennes, France. simon.esneault@univ-rennes1.fr
Simon
S
Esneault
Cyril
C
Lafon
Jean-Louis
JL
Dillenseger
D000465:Algorithms; D006528:Carcinoma, Hepatocellular / Q000098:blood supply / Q000000981:diagnostic imaging; D003198:Computer Simulation; D006503:Hepatic Veins / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008099:Liver / Q000098:blood supply* / Q000000981:diagnostic imaging; D008113:Liver Neoplasms / Q000098:blood supply / Q000000981:diagnostic imaging; D019047:Phantoms, Imaging; D011860:Radiography, Abdominal; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014463:Ultrasonography