Image descriptors in angiography

Katharina Hofschen; Timo Geissler; Nicola Rieke; Christian Schulte zu Berge; Nassir Navab; Stefanie Demirci

doi:10.1007/978-3-662-49465-3_50

Image descriptors in angiography

Katharina Hofschen, Timo Geissler, Nicola Rieke, Christian Schulte zu Berge, Nassir Navab, Stefanie Demirci

Informatics 16 - Chair of Computer Aided Medical Procedures

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Despite recent advances in the field of image-guided interventions (IGI), the bottleneck for Angiography/X-ray guided procedures in particular is accurate and robust 2D-3D image alignment. The conventional, straight-forward parameter optimization approach is known to be ill-posed and less efficient. Retrieval-based approaches may be of superior choice here. However, this requires salient and robust image features, which can handle the difficulties of Angiographic images such as high level of noise and contrast variance. In this paper, we investigate state-of-the-art features of the field of computer vision regarding the applicability and reliability in the challenging scenario of Angiography.

Original language	English
Title of host publication	Bildverarbeitung fur die Medizin 2016
Subtitle of host publication	Algorithmen – Systeme – Anwendungen - Proceedings des Workshops
Editors	Thomas M. Deserno, Heinz Handels, Thomas Tolxdorff, Hans-Peter Meinzer
Publisher	Kluwer Academic Publishers
Pages	283-288
Number of pages	6
ISBN (Print)	9783662494646
DOIs	https://doi.org/10.1007/978-3-662-49465-3_50
State	Published - 2017
Event	Workshops on Image processing for the medicine, 2016 - Berlin, Germany Duration: 13 Mar 2016 → 15 Mar 2016

Publication series

Name	Informatik aktuell
ISSN (Print)	1431-472X

Conference

Conference	Workshops on Image processing for the medicine, 2016
Country/Territory	Germany
City	Berlin
Period	13/03/16 → 15/03/16

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10.1007/978-3-662-49465-3_50

Cite this

Hofschen, K., Geissler, T., Rieke, N., zu Berge, C. S., Navab, N., & Demirci, S. (2017). Image descriptors in angiography. In T. M. Deserno, H. Handels, T. Tolxdorff, & H.-P. Meinzer (Eds.), Bildverarbeitung fur die Medizin 2016: Algorithmen – Systeme – Anwendungen - Proceedings des Workshops (pp. 283-288). (Informatik aktuell). Kluwer Academic Publishers. https://doi.org/10.1007/978-3-662-49465-3_50

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title = "Image descriptors in angiography",

abstract = "Despite recent advances in the field of image-guided interventions (IGI), the bottleneck for Angiography/X-ray guided procedures in particular is accurate and robust 2D-3D image alignment. The conventional, straight-forward parameter optimization approach is known to be ill-posed and less efficient. Retrieval-based approaches may be of superior choice here. However, this requires salient and robust image features, which can handle the difficulties of Angiographic images such as high level of noise and contrast variance. In this paper, we investigate state-of-the-art features of the field of computer vision regarding the applicability and reliability in the challenging scenario of Angiography.",

author = "Katharina Hofschen and Timo Geissler and Nicola Rieke and {zu Berge}, {Christian Schulte} and Nassir Navab and Stefanie Demirci",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2016.; Workshops on Image processing for the medicine, 2016 ; Conference date: 13-03-2016 Through 15-03-2016",

year = "2017",

doi = "10.1007/978-3-662-49465-3_50",

language = "English",

isbn = "9783662494646",

series = "Informatik aktuell",

publisher = "Kluwer Academic Publishers",

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booktitle = "Bildverarbeitung fur die Medizin 2016",

}

Hofschen, K, Geissler, T, Rieke, N, zu Berge, CS, Navab, N & Demirci, S 2017, Image descriptors in angiography. in TM Deserno, H Handels, T Tolxdorff & H-P Meinzer (eds), Bildverarbeitung fur die Medizin 2016: Algorithmen – Systeme – Anwendungen - Proceedings des Workshops. Informatik aktuell, Kluwer Academic Publishers, pp. 283-288, Workshops on Image processing for the medicine, 2016, Berlin, Germany, 13/03/16. https://doi.org/10.1007/978-3-662-49465-3_50

Image descriptors in angiography. / Hofschen, Katharina; Geissler, Timo; Rieke, Nicola et al.
Bildverarbeitung fur die Medizin 2016: Algorithmen – Systeme – Anwendungen - Proceedings des Workshops. ed. / Thomas M. Deserno; Heinz Handels; Thomas Tolxdorff; Hans-Peter Meinzer. Kluwer Academic Publishers, 2017. p. 283-288 (Informatik aktuell).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Image descriptors in angiography

AU - Hofschen, Katharina

AU - Geissler, Timo

AU - Rieke, Nicola

AU - zu Berge, Christian Schulte

AU - Navab, Nassir

AU - Demirci, Stefanie

N1 - Publisher Copyright: © Springer-Verlag Berlin Heidelberg 2016.

PY - 2017

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N2 - Despite recent advances in the field of image-guided interventions (IGI), the bottleneck for Angiography/X-ray guided procedures in particular is accurate and robust 2D-3D image alignment. The conventional, straight-forward parameter optimization approach is known to be ill-posed and less efficient. Retrieval-based approaches may be of superior choice here. However, this requires salient and robust image features, which can handle the difficulties of Angiographic images such as high level of noise and contrast variance. In this paper, we investigate state-of-the-art features of the field of computer vision regarding the applicability and reliability in the challenging scenario of Angiography.

AB - Despite recent advances in the field of image-guided interventions (IGI), the bottleneck for Angiography/X-ray guided procedures in particular is accurate and robust 2D-3D image alignment. The conventional, straight-forward parameter optimization approach is known to be ill-posed and less efficient. Retrieval-based approaches may be of superior choice here. However, this requires salient and robust image features, which can handle the difficulties of Angiographic images such as high level of noise and contrast variance. In this paper, we investigate state-of-the-art features of the field of computer vision regarding the applicability and reliability in the challenging scenario of Angiography.

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DO - 10.1007/978-3-662-49465-3_50

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SP - 283

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BT - Bildverarbeitung fur die Medizin 2016

A2 - Deserno, Thomas M.

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PB - Kluwer Academic Publishers

T2 - Workshops on Image processing for the medicine, 2016

Y2 - 13 March 2016 through 15 March 2016

ER -

Image descriptors in angiography

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