Deformable 2D-3D registration of the pelvis with a limited field of view, using shape statistics.
Our paper summarizes experiments for measuring the accuracy of deformable 2D-3D registration between sets of simulated x-ray images (DRR's) and a statistical shape model of the pelvis bones, which includes x-ray attenuation information ("density"). In many surgical scenarios, the images contain a truncated view of the pelvis anatomy. Our work specifically addresses this problem by examining different selections of truncated views as target images. Our atlas is derived by applying principal component analysis to a population of up to 110 instance shapes. The experiments measure the registration error with a large and truncated FOV. A typical accuracy of about 2 mm is achieved in the 2D-3D registration, compared with about 1.4 mm of an "optimal" 3D-3D registration.
Sadowsky
Ofri
O
Department of Computer Science, Johns Hopkins University, USA. ofri@cs.jhu.edu
Chintalapani
Gouthami
G
Taylor
Russell H
RH
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D010384:Pelvic Bones / Q000000981:diagnostic imaging*; 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; D014057:Tomography, X-Ray Computed / Q000379:methods*