A statistical motion model based on biomechanical simulations for data fusion during image-guided prostate interventions.
A method is described for generating a patient-specific, statistical motion model (SMM) of the prostate gland. Finite element analysis (FEA) is used to simulate the motion of the gland using an ultrasound-based 3D FE model over a range of plausible boundary conditions and soft-tissue properties. By applying principal component analysis to the displacements of the FE mesh node points inside the gland, the simulated deformations are then used as training data to construct the SMM. The SMM is used to both predict the displacement field over the whole gland and constrain a deformable surface registration algorithm, given only a small number of target points on the surface of the deformed gland. Using 3D transrectal ultrasound images of the prostates of five patients, acquired before and after imposing a physical deformation, to evaluate the accuracy of predicted landmark displacements, the mean target registration error was found to be less than 1.9 mm.
Hu
Yipeng
Y
Centre for Medical Image Computing, University College London, London, UK.
Morgan
Dominic
D
Ahmed
Hashim Uddin
HU
Pendsé
Doug
D
Sahu
Mahua
M
Allen
Clare
C
Emberton
Mark
M
Hawkes
David
D
Barratt
Dean
D
D016477:Artifacts; D055592:Biophysical Phenomena; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D009038:Motion; D011468:Prostatectomy / Q000379:methods; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000601:surgery*; D025321:Surgery, Computer-Assisted / Q000379:methods; D018084:Ultrasonography, Interventional / Q000379:methods*