title: Alignment of sparse freehand 3-D ultrasound with preoperative images of the liver using models of respiratory motion and deformation.
abstract: We present a method for alignment of an interventional plan to optically tracked two-dimensional intraoperative ultrasound (US) images of the liver. Our clinical motivation is to enable the accurate transfer of information from three-dimensional preoperative imaging modalities [magnetic resonance (MR) or computed tomography (CT)] to intraoperative US to aid needle placement for thermal ablation of liver metastases. An initial rigid registration to intraoperative coordinates is obtained using a set of US images acquired at maximum exhalation. A preprocessing step is applied to both the preoperative images and the US images to produce evidence of corresponding structures. This yields two sets of images representing classification of regions as vessels. The registration then proceeds using these images. The preoperative images and plan are then warped to correspond to a single US slice acquired at an unknown point in the breathing cycle where the liver is likely to have moved and deformed relative to the preoperative image. Alignment is constrained using a patient-specific model of breathing motion and deformation. Target registration error is estimated by carrying out simulation experiments using resliced MR volumes to simulate real US and comparing the registration results to a "bronze-standard" registration performed on the full MR volume. Finally, the system is tested using real US and verified using visual inspection.
authors.affiliation: Computational Imaging Science Group, Division of Imaging Sciences, Guy's King's and St. Thomas' Medical School, King's College London, London, UK. j.blackall@ucl.ac.uk
authors.forename: Jane M
authors.initials: JM
authors.lastname: Blackall
authors.forename: Graeme P
authors.initials: GP
authors.lastname: Penney
authors.forename: Andrew P
authors.initials: AP
authors.lastname: King
authors.forename: David J
authors.initials: DJ
authors.lastname: Hawkes
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D003198:Computer Simulation; D004548:Elasticity; D006498:Hepatectomy / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000295:instrumentation / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008099:Liver / Q000000981:diagnostic imaging* / Q000473:pathology / Q000601:surgery*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008954:Models, Biological; D009068:Movement; D019047:Phantoms, Imaging; D011300:Preoperative Care / Q000379:methods; D015203:Reproducibility of Results; D015656:Respiratory Mechanics; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014463:Ultrasonography / Q000379:methods*; D014584:User-Computer Interface