Numerical algorithms for spatial registration of line fiducials from cross-sectional images.
We present several numerical algorithms for six-degree-of-freedom rigid-body registration of line fiducial objects to their marks in cross-sectional planar images, such as those obtained in CT and MRI, given the correspondence between the marks and line fiducials. The area of immediate application is frame-based stereotactic procedures, such as radiosurgery and functional neurosurgery. The algorithms are also suitable to problems where the fiducial pattern moves inside the imager, as is the case in robot-assisted image-guided surgical applications. We demonstrate the numerical methods on clinical CT images and computer-generated data and compare their performance in terms of robustness to missing data, robustness to noise, and speed. The methods show two unique strengths: (1) They provide reliable registration of incomplete fiducial patterns when up to two-thirds of the total fiducials are missing from the image; and (2) they are applicable to an arbitrary combination of line fiducials without algorithmic modification. The average speed of the fastest algorithm is 0.3236 s for six fiducial lines in real CT data in a Matlab implementation.
Sangyoon
S
Lee
Gabor
G
Fichtinger
Gregory S
GS
Chirikjian
D000465:Algorithms; D019412:Anatomy, Cross-Sectional / Q000379:methods; D006257:Head / Q000033:anatomy & histology* / Q000000981:diagnostic imaging*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D011786:Quality Control; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013238:Stereotaxic Techniques; D013269:Stochastic Processes; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*