Evaluating an optical-flow-based registration algorithm for contrast-enhanced magnetic resonance imaging of the breast.
Dynamic contrast-enhanced magnetic resonance imaging studies of the breast are frequently degraded by patient motion. In order to correct for this, any registration algorithm must overcome two major challenges: the highly deformable nature of the breast itself and the need to remove changes in signal intensity due to patient motion whilst leaving potentially significant changes in signal intensity due to changes in contrast agent concentration unchanged. In this paper, we evaluate the use of a non-rigid registration method that uses optical flow equations to drive the displacement of a grid of control points. With conventional optical flow techniques it is assumed that changes in image intensity are solely due to motion, making it unsuitable for use with contrast-enhanced studies. The registration algorithm evaluated in this paper overcomes this problem by including an additional term to account for changes in image intensity. Studies simulating physiologically plausible deformations of the breast together with realistic changes in contrast-enhancement derived from patient studies demonstrate that the algorithm is capable of registering images to sub-voxel accuracy within minutes. This technique has now been successfully incorporated into a breast cancer screening protocol allowing registered images to be provided routinely to the radiologist immediately after the scanning session.
Martel
A L
AL
Imaging Research, Sunnybrook Health Sciences Centre, Toronto, ON, M4N 3M5, Canada. anne.martel@sri.utoronto.ca
Froh
M S
MS
Brock
K K
KK
Plewes
D B
DB
Barber
D C
DC
D000465:Algorithms; D001696:Biomechanical Phenomena / Q000379:methods; D001940:Breast / Q000473:pathology*; D001943:Breast Neoplasms / Q000175:diagnosis / Q000000981:diagnostic imaging* / Q000473:pathology*; D003198:Computer Simulation; D003287:Contrast Media / Q000737:chemistry / Q000494:pharmacology*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008962:Models, Theoretical; D055095:Optics and Photonics; D010363:Pattern Recognition, Automated; D011857:Radiographic Image Interpretation, Computer-Assisted; D013382:Subtraction Technique
D003287:Contrast Media