Four dimensional MR image analysis of dynamic renography.
A novel four dimensional image analysis approach including registration and segmentation of dynamic contrast enhanced renal MR images is presented. This integrated method is motivated by the observation of the reciprocity between registration and segmentation in 4D time-series images. Fully automated Fourier-based registration with sub-voxel accuracy and semi-automated time-series segmentation were intertwined to improve the accuracy in a multi-step fashion. We have tested our algorithm on several real patient data sets. Clinical validation showed remarkable and consistent agreement between the proposed method and manual segmentation by experts.
Song
Ting
T
Dept. of Biomed. Eng., Columbia Univ., New York, NY 10027, USA. ts2060@columbia.edu
Lee
Vivian S
VS
Rusinek
Henry
H
Wong
Samson
S
Laine
Andrew F
AF
D000465:Algorithms; D001698:Biomedical Engineering; D003287:Contrast Media; D005583:Fourier Analysis; D019786:Gadolinium DTPA; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D021621:Imaging, Three-Dimensional; D007677:Kidney Function Tests / Q000379:methods* / Q000706:statistics & numerical data; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data; D011866:Radioisotope Renography / Q000379:methods* / Q000706:statistics & numerical data
D003287:Contrast Media; D019786:Gadolinium DTPA