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Original scientific paper

Voxel-Based Similarity Measures for Medical Image Registration in Radiological Diagnosis and Image Guided Surgery

Thorsten M. Buzug ; Philips Research Laboratories, Division Technical Systems, Hamburg, Germany
Jurgen Weese ; Philips Research Laboratories, Division Technical Systems, Hamburg, Germany

Fulltext: english, pdf (8 MB) pages 165-179 downloads: 133* cite
APA 6th Edition
Buzug, T.M. & Weese, J. (1998). Voxel-Based Similarity Measures for Medical Image Registration in Radiological Diagnosis and Image Guided Surgery. Journal of computing and information technology, 6 (2), 165-179. Retrieved from https://hrcak.srce.hr/150232
MLA 8th Edition
Buzug, Thorsten M. and Jurgen Weese. "Voxel-Based Similarity Measures for Medical Image Registration in Radiological Diagnosis and Image Guided Surgery." Journal of computing and information technology, vol. 6, no. 2, 1998, pp. 165-179. https://hrcak.srce.hr/150232. Accessed 10 Jul. 2020.
Chicago 17th Edition
Buzug, Thorsten M. and Jurgen Weese. "Voxel-Based Similarity Measures for Medical Image Registration in Radiological Diagnosis and Image Guided Surgery." Journal of computing and information technology 6, no. 2 (1998): 165-179. https://hrcak.srce.hr/150232
Harvard
Buzug, T.M., and Weese, J. (1998). 'Voxel-Based Similarity Measures for Medical Image Registration in Radiological Diagnosis and Image Guided Surgery', Journal of computing and information technology, 6(2), pp. 165-179. Available at: https://hrcak.srce.hr/150232 (Accessed 10 July 2020)
Vancouver
Buzug TM, Weese J. Voxel-Based Similarity Measures for Medical Image Registration in Radiological Diagnosis and Image Guided Surgery. Journal of computing and information technology [Internet]. 1998 [cited 2020 July 10];6(2):165-179. Available from: https://hrcak.srce.hr/150232
IEEE
T.M. Buzug and J. Weese, "Voxel-Based Similarity Measures for Medical Image Registration in Radiological Diagnosis and Image Guided Surgery", Journal of computing and information technology, vol.6, no. 2, pp. 165-179, 1998. [Online]. Available: https://hrcak.srce.hr/150232. [Accessed: 10 July 2020]

Abstracts
Registration of images is a key technique for numerous medical applications from diagnosis to image guided therapy. In the present paper we focus on gray-value based registration methods. Of special interest is the so-called similarity measure which must be optimized. It is the intention of the paper to emphasize the fact that a successful registration requires a similarity measure that is carefully chosen with respect to the underlying medical application. Two single-modality examples are presented in the paper, i.e. the diagnostic tool of digital subtraction angiography and an intervention guidance under X-ray fluoroscopic control. We discuss new similarity measures, i.e. the class of one-dimensional hi stogram based measures and the pattern intensity, designed for these applications and compare them with frequently used measures like the cross-correlation function , cross-structure function and deterministic sign change criterion. It is demonstrated that the results obtained with the new measures are superior to the results obtained with the latter mentioned ones.

Keywords
image registration; single modality; similarity measure; pattern intensity; energy; digital subtraction angiography; image guided surgery

Hrčak ID: 150232

URI
https://hrcak.srce.hr/150232

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