title: MR to ultrasound image registration for guiding prostate biopsy and interventions.
abstract: A method is described for registering preoperative magnetic resonance (MR) to intraoperative transrectal ultrasound (TRUS) images of the prostate gland. A statistical motion model (SMM) of the prostate is first built using training data provided by biomechanical simulations of the motion of a patient-specific finite element model, derived from a preoperative MR image. The SMM is then registered to a 3D TRUS image by maximising the likelihood of the shape of an SMM instance given a voxel-intensity-based feature, which represents an estimate of normal vector at the surface of the prostate gland. Using data acquired from 7 patients, the accuracy of registering T2 MR to 3D TRUS images was evaluated using anatomical landmarks inside the gland. The results show that the proposed registration method has a root-mean-square target registration error of 2.66 mm.
authors.affiliation: Centre for Medical Image Computing, University College London, London, UK.
authors.forename: Yipeng
authors.initials: Y
authors.lastname: Hu
authors.forename: Hashim Uddin
authors.initials: HU
authors.lastname: Ahmed
authors.forename: Clare
authors.initials: C
authors.lastname: Allen
authors.forename: Doug
authors.initials: D
authors.lastname: Pendsé
authors.forename: Mahua
authors.initials: M
authors.lastname: Sahu
authors.forename: Mark
authors.initials: M
authors.lastname: Emberton
authors.forename: David
authors.initials: D
authors.lastname: Hawkes
authors.forename: Dean
authors.initials: D
authors.lastname: Barratt
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001706:Biopsy / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D011471:Prostatic Neoplasms / Q000175:diagnosis*; D015641:Radiography, Interventional / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D025321:Surgery, Computer-Assisted / Q000379:methods*