TY - JOUR
T1 - Evaluating similarity measure for multimodal 3D to 2D registration
AU - Kiran, Usha
AU - Ramakrishna Naik, Roshan
AU - Bhat, Shyamasunder N.
AU - H, Anitha
N1 - Funding Information:
The authors acknowledge the Manipal Academy of Higher Education (MAHE), Manipal, for supporting the part of the work to register for a patent titled ‘A 3D-2D Registration Framework for Multimodel Imaging’ in Indian Patent Office on January 10, 2023, Application Number 202341002076. The authors also thankful to the Department of Radiology and Orthopaedics- Kasturba Medical College and Hospital, Manipal, Karnataka for providing the spinal dataset.
Publisher Copyright:
© 2023 IOP Publishing Ltd
PY - 2023/9
Y1 - 2023/9
N2 - The 3D to 2D registration technique in spine surgery is vital to aid surgeons in avoiding the wrong site surgery by estimating the vertebral pose. The vertebral poses are estimated by generating the spatial correspondence relationship between pre-operative MR with intra-operative x-ray images, then evaluated using a similarity measure. Different similarity measures are used in 3D to 2D registration techniques to assess the spatial correspondence between the pre-operative and intra-operative images. However, to evaluate the registration performance of the similarity measures, the proposed framework employs three different similarity measures: Binary Image Matching, Dice Coefficients, and Normalized Cross-correlation technique to compare the images based on pixel positions. The registration accuracy of the proposed similarity measures is compared based on the mean Target Registration Error, mean Iteration Times, and success rate. In the absence of simulated test images, the experiment is conducted on the simulated AP and Lateral test images. The experiment conducted on the simulated test images shows that all three similarity measures work well for the feature based 3D to 2D registration in that BIM gives better results. The experiment also indicates high registration accuracy when the initial displacements are varied up to ±20 mm and ±100of the translational and rotational parameters, respectively, for three similarity measures.
AB - The 3D to 2D registration technique in spine surgery is vital to aid surgeons in avoiding the wrong site surgery by estimating the vertebral pose. The vertebral poses are estimated by generating the spatial correspondence relationship between pre-operative MR with intra-operative x-ray images, then evaluated using a similarity measure. Different similarity measures are used in 3D to 2D registration techniques to assess the spatial correspondence between the pre-operative and intra-operative images. However, to evaluate the registration performance of the similarity measures, the proposed framework employs three different similarity measures: Binary Image Matching, Dice Coefficients, and Normalized Cross-correlation technique to compare the images based on pixel positions. The registration accuracy of the proposed similarity measures is compared based on the mean Target Registration Error, mean Iteration Times, and success rate. In the absence of simulated test images, the experiment is conducted on the simulated AP and Lateral test images. The experiment conducted on the simulated test images shows that all three similarity measures work well for the feature based 3D to 2D registration in that BIM gives better results. The experiment also indicates high registration accuracy when the initial displacements are varied up to ±20 mm and ±100of the translational and rotational parameters, respectively, for three similarity measures.
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U2 - 10.1088/2057-1976/ace9e1
DO - 10.1088/2057-1976/ace9e1
M3 - Article
C2 - 37487480
AN - SCOPUS:85166442652
SN - 2057-1976
VL - 9
JO - Biomedical physics & engineering express
JF - Biomedical physics & engineering express
IS - 5
M1 - 055015
ER -