Automatic registration of pelvic computed tomography data and magnetic resonance scans including a full circle method for quantitative accuracy evaluation.
The purpose of this study is to develop a method for registration of CT and MR scans of the pelvis with minimal user interaction and to obtain a means for objective quantification of the registration accuracy of clinical data without markers. CT scans were registered with proton density MR scans using chamfer matching on automatically segmented bone. A fixed threshold was used to segment CT, while morphological filters were used to segment MR. The method was tested with transverse and coronal MR scans of 18 patients and sagittal MR scans of 8 patients. The registration accuracy was estimated by comparing (triangulating) registrations of a single CT scan with MR in different orientations in a "full circle." For example, CT is first matched on transverse MR, next transverse MR is matched independently on coronal MR, and finally coronal MR is matched independently on CT. The product of the three transformations is the identity if all matching steps are perfect. Deviations from identity occur both due to random errors and due to some types of systematic errors. MR was registered on MR (to close the "circle") by minimization of rms voxel value differences. CT-MR registration takes about 1 min, including user interaction. The random error for CT-MR registration with transverse or coronal MR was 0.5 mm in translation and 0.4 degree in rotation (standard deviation) for each axis. A systematic registration error of about 1 mm was demonstrated along the MR frequency encoding direction, which is attributed to the chemical shift. In conclusion, the presented algorithm efficiently and accurately registers pelvic CT and MR scans on bone. The "full circle" method provides an estimate of the registration accuracy on clinical data.
van Herk
M
M
Radiotherapy Department, The Netherlands Cancer Institute/Antoni van Leeuwenhoek Huis, Amsterdam, The Netherlands. portal@nki.nl
de Munck
J C
JC
Lebesque
J V
JV
Muller
S
S
Rasch
C
C
Touw
A
A
D000465:Algorithms; D000704:Analysis of Variance; D055592:Biophysical Phenomena; D001703:Biophysics; D005069:Evaluation Studies as Topic; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods / Q000706:statistics & numerical data; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data; D008297:Male; D010388:Pelvis / Q000000981:diagnostic imaging* / Q000473:pathology*; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology; D011856:Radiographic Image Enhancement / Q000379:methods; D014057:Tomography, X-Ray Computed / Q000379:methods* / Q000706:statistics & numerical data