Novel algorithms for robust registration of fiducials in CT and MRI

Sangyoon Lee, Gabor Fichtinger, Gregory S. Chirikjian

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

Abstract

In this paper we present several numerical algorithms for registering fiducials in planar CT or MRI images to their corresponding three-dimensional locations. The unique strength of these methods is their ability to robustly handle incomplete fiducials patterns, even in extreme cases when as much as one third of the fiducial data is missing from the images. We compare the effectiveness of these algorithms in terms of flops and robustness on actual CT data sets.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages717-724
Number of pages8
Volume2208
ISBN (Print)3540426973, 9783540454687
DOIs
StatePublished - 2001
Event4th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2001 - Utrecht, Netherlands
Duration: Oct 14 2001Oct 17 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2208
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other4th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2001
CountryNetherlands
CityUtrecht
Period10/14/0110/17/01

Fingerprint

Magnetic resonance imaging
Registration
Numerical Algorithms
Extremes
Robustness
Three-dimensional

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Lee, S., Fichtinger, G., & Chirikjian, G. S. (2001). Novel algorithms for robust registration of fiducials in CT and MRI. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2208, pp. 717-724). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2208). Springer Verlag. https://doi.org/10.1007/3-540-45468-3_86

Novel algorithms for robust registration of fiducials in CT and MRI. / Lee, Sangyoon; Fichtinger, Gabor; Chirikjian, Gregory S.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 2208 Springer Verlag, 2001. p. 717-724 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2208).

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

Lee, S, Fichtinger, G & Chirikjian, GS 2001, Novel algorithms for robust registration of fiducials in CT and MRI. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 2208, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2208, Springer Verlag, pp. 717-724, 4th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2001, Utrecht, Netherlands, 10/14/01. https://doi.org/10.1007/3-540-45468-3_86
Lee S, Fichtinger G, Chirikjian GS. Novel algorithms for robust registration of fiducials in CT and MRI. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 2208. Springer Verlag. 2001. p. 717-724. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/3-540-45468-3_86
Lee, Sangyoon ; Fichtinger, Gabor ; Chirikjian, Gregory S. / Novel algorithms for robust registration of fiducials in CT and MRI. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 2208 Springer Verlag, 2001. pp. 717-724 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{52cd1295e9ba4b6a821d3dd9e2f45277,
title = "Novel algorithms for robust registration of fiducials in CT and MRI",
abstract = "In this paper we present several numerical algorithms for registering fiducials in planar CT or MRI images to their corresponding three-dimensional locations. The unique strength of these methods is their ability to robustly handle incomplete fiducials patterns, even in extreme cases when as much as one third of the fiducial data is missing from the images. We compare the effectiveness of these algorithms in terms of flops and robustness on actual CT data sets.",
author = "Sangyoon Lee and Gabor Fichtinger and Chirikjian, {Gregory S.}",
year = "2001",
doi = "10.1007/3-540-45468-3_86",
language = "English (US)",
isbn = "3540426973",
volume = "2208",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "717--724",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Novel algorithms for robust registration of fiducials in CT and MRI

AU - Lee, Sangyoon

AU - Fichtinger, Gabor

AU - Chirikjian, Gregory S.

PY - 2001

Y1 - 2001

N2 - In this paper we present several numerical algorithms for registering fiducials in planar CT or MRI images to their corresponding three-dimensional locations. The unique strength of these methods is their ability to robustly handle incomplete fiducials patterns, even in extreme cases when as much as one third of the fiducial data is missing from the images. We compare the effectiveness of these algorithms in terms of flops and robustness on actual CT data sets.

AB - In this paper we present several numerical algorithms for registering fiducials in planar CT or MRI images to their corresponding three-dimensional locations. The unique strength of these methods is their ability to robustly handle incomplete fiducials patterns, even in extreme cases when as much as one third of the fiducial data is missing from the images. We compare the effectiveness of these algorithms in terms of flops and robustness on actual CT data sets.

UR - http://www.scopus.com/inward/record.url?scp=84958156617&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84958156617&partnerID=8YFLogxK

U2 - 10.1007/3-540-45468-3_86

DO - 10.1007/3-540-45468-3_86

M3 - Conference contribution

AN - SCOPUS:84958156617

SN - 3540426973

SN - 9783540454687

VL - 2208

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 717

EP - 724

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

PB - Springer Verlag

ER -