An atlas-based segmentation propagation framework locally affine registration--application to automatic whole heart segmentation.
In this paper, we present a novel registration algorithm for locally affine registrations. This method preserves the anatomical and intensity class relationships between the local regions. A regularisation procedure is used to maintain a global diffeomorphic transformation. Combined with a novel generic method for accurately inverting the final deformation field, we include our techniques within an atlas-based segmentation propagation framework. We applied our method to automatically segment the whole heart from cardiac magnetic resonance images from a cohort of 18 volunteers (acquisition resolution 2 x 2 x 2 mm). The results show that the proposed method provides a robust initialisation for the atlas-based segmentation propagation framework refined with a fluid registration. We validated our approach against other registration strategies, and demonstrated that we improved the accuracy of the whole heart segmentations (1.8 +/- 0.42 mm).
Zhuang
Xiahai
X
Centre for Medical Image Computing, Med Phys Dept, UCL, WC 1E 6BT, UK. x.zhuang@ucl.ac.uk
Rhode
Kawal
K
Arridge
Simon
S
Razavi
Reza
R
Hill
Derek
D
Hawkes
David
D
Ourselin
Sebastien
S
D000465:Algorithms; D001185:Artificial Intelligence; D006321:Heart / Q000033:anatomy & histology*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique