Image-to-physical registration for image-guided interventions using 3-D ultrasound and an ultrasound imaging model.
We present a technique for automatic intensity-based image-to-physical registration of a 3-D segmentation for image-guided interventions. The registration aligns the segmentation with tracked and calibrated 3-D ultrasound (US) images of the target region. The technique uses a probabilistic framework and explicitly incorporates a model of the US image acquisition process. The rigid body registration parameters are varied to maximise the likelihood that the real US image(s) were formed using the US imaging model from the probe transducer position. The proposed technique is validated on images segmented from cardiac magnetic resonance imaging (MRI) data and 3-D US images acquired from 3 volunteers and 1 patient. We show that the accuracy of the algorithm is 2.6-4.2mm and the capture range is 9-18mm. The proposed technique has the potential to provide accurate image-to-physical registrations for a range of image guidance applications.
King
Andrew P
AP
Division of Imaging Sciences, King's College London, UK. andrew.king@kcl.ac.uk
Ma
Ying-Liang
YL
Yao
Cheng
C
Jansen
Christian
C
Razavi
Reza
R
Rhode
Kawal S
KS
Penney
Graeme P
GP
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D025321:Surgery, Computer-Assisted / Q000379:methods*; D018084:Ultrasonography, Interventional / Q000379:methods*