Efficient Similarity Measurement between Digitally Reconstructed Radiograph and Fluoroscopy for 3D-2D Registration

B. H.Rao Chaitanya, H. Anitha, N. Bhat Shyamasunder, Vidya Bhat

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This work aims to make use of compressed sensing to exploit the redundant nature hidden in the image and reduce the computational complexity involved in DRR generation. As a result, radiation risk to the patient can be reduced whilst maintaining an acceptable level of accuracy thus resulting in speed-up in DRR generation using the multi-resolution approach compared to the conventional ray casting approach. Also in this research, different gradient based similarity metrics were compared on the basis of accuracy to achieve robustness against image content mismatch.

Original languageEnglish
Title of host publication2018 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages611-616
Number of pages6
ISBN (Electronic)9781538653142
DOIs
Publication statusPublished - 30-11-2018
Event7th International Conference on Advances in Computing, Communications and Informatics, ICACCI 2018 - Bangalore, India
Duration: 19-09-201822-09-2018

Conference

Conference7th International Conference on Advances in Computing, Communications and Informatics, ICACCI 2018
CountryIndia
CityBangalore
Period19-09-1822-09-18

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems

Cite this

Chaitanya, B. H. R., Anitha, H., Shyamasunder, N. B., & Bhat, V. (2018). Efficient Similarity Measurement between Digitally Reconstructed Radiograph and Fluoroscopy for 3D-2D Registration. In 2018 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2018 (pp. 611-616). [8554401] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACCI.2018.8554401