title: A new registration/visualization paradigm for CT-fluoroscopy guided RF liver ablation.
abstract: 2D-3D slice-to-volume registration for abdominal organs like liver is difficult due to the breathing motion and tissue deformation. The purpose of our approach is to ease CT-fluoroscopy (CT-fluoro) based needle insertion for the Radiofrequency Liver Ablation procedure using high resolution contrasted preoperative data. In this case, low signal-to-noise ratio, absence of contrast and additional presence of needle in CT-fluoro makes it difficult to guarantee the solution of any deformable slice-to-volume registration algorithm. In this paper, we first propose a method for creating a set of ground truth (GT) simulation data based on a non-linear deformation of the CT-fluoro volume obtained from real patients. Second, we split the CT-fluoro image and apply intensity based rigid and affine registration to each section. We then propose a novel solution, which consists of intuitive visualization sequences of optimal sub-volumes of preinterventional data based on the registration results. Experiments on synthetic and real patient data and direct feedback of two interventionalists validate our alternative approach.
authors.affiliation: Chair for Computer Aided Medical Procedures, TU Munich, Germany. micu@cs.tum.edu
authors.forename: Ruxandra
authors.initials: R
authors.lastname: Micu
authors.forename: Tobias F
authors.initials: TF
authors.lastname: Jakobs
authors.forename: Martin
authors.initials: M
authors.lastname: Urschler
authors.forename: Nassir
authors.initials: N
authors.lastname: Navab
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D017115:Catheter Ablation / Q000379:methods*; D005471:Fluoroscopy / Q000379:methods; D006498:Hepatectomy / Q000379:methods*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D008099:Liver / Q000000981:diagnostic imaging / Q000601:surgery; D008113:Liver Neoplasms / Q000000981:diagnostic imaging* / Q000601:surgery*; D010363:Pattern Recognition, Automated / Q000379:methods; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D025321:Surgery, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014584:User-Computer Interface