Scale and curvature invariant ridge detector for tortuous and fragmented structures

Roberto Annunziata; Ahmad Kheirkhah; Pedram Hamrah; Emanuele Trucco

doi:10.1007/978-3-319-24574-4_70

Scale and curvature invariant ridge detector for tortuous and fragmented structures

Roberto Annunziata (Lead / Corresponding author), Ahmad Kheirkhah, Pedram Hamrah, Emanuele Trucco

Computing

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

28 Citations (Scopus)

Abstract

Segmenting dendritic trees and corneal nerve fibres is challenging due to their uneven and irregular appearance in the respective image modalities. State-of-the-art approaches use hand-crafted features based on local assumptions that are often violated by tortuous and point-like structures, e.g., straight tubular shape. We propose a novel ridge detector, SCIRD, which is simultaneously rotation, scale and curvature invariant, and relaxes shape assumptions to achieve enhancement of target image structures. Experimental results on three datasets show that our approach outperforms state-of-the-art hand-crafted methods on tortuous and point-like structures, especially when captured at low resolution or limited signal-to-noise ratio and in the presence of other non-target structures.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015
Subtitle of host publication	18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III
Editors	Nassir Navab, Joachim Hornegger, William M. Wells, Alejandro F. Frangi
Publisher	Springer International Publishing
Pages	588-595
Number of pages	8
ISBN (Electronic)	9783319245744
ISBN (Print)	9783319245737
DOIs	https://doi.org/10.1007/978-3-319-24574-4_70
Publication status	Published - 18 Nov 2015
Event	18th International Conference on Medical Image Computing and Computer Assisted Interventions - Philharmonic Hall, Munich, Germany Duration: 5 Oct 2015 → 9 Oct 2015 https://www.miccai2015.org/

Publication series

Name	Lecture notes in computer science
Publisher	Springer International Publishing
Volume	9351
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Conference on Medical Image Computing and Computer Assisted Interventions
Abbreviated title	MICCAI 2015
Country/Territory	Germany
City	Munich
Period	5/10/15 → 9/10/15
Internet address	https://www.miccai2015.org/

ASJC Scopus subject areas

General Computer Science
Theoretical Computer Science

Access to Document

10.1007/978-3-319-24574-4_70

Cite this

Annunziata, R., Kheirkhah, A., Hamrah, P., & Trucco, E. (2015). Scale and curvature invariant ridge detector for tortuous and fragmented structures. In N. Navab, J. Hornegger, W. M. Wells, & A. F. Frangi (Eds.), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III (pp. 588-595). (Lecture notes in computer science; Vol. 9351). Springer International Publishing. https://doi.org/10.1007/978-3-319-24574-4_70

Annunziata, Roberto ; Kheirkhah, Ahmad ; Hamrah, Pedram et al. / Scale and curvature invariant ridge detector for tortuous and fragmented structures. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III. editor / Nassir Navab ; Joachim Hornegger ; William M. Wells ; Alejandro F. Frangi . Springer International Publishing, 2015. pp. 588-595 (Lecture notes in computer science).

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title = "Scale and curvature invariant ridge detector for tortuous and fragmented structures",

abstract = "Segmenting dendritic trees and corneal nerve fibres is challenging due to their uneven and irregular appearance in the respective image modalities. State-of-the-art approaches use hand-crafted features based on local assumptions that are often violated by tortuous and point-like structures, e.g., straight tubular shape. We propose a novel ridge detector, SCIRD, which is simultaneously rotation, scale and curvature invariant, and relaxes shape assumptions to achieve enhancement of target image structures. Experimental results on three datasets show that our approach outperforms state-of-the-art hand-crafted methods on tortuous and point-like structures, especially when captured at low resolution or limited signal-to-noise ratio and in the presence of other non-target structures.",

author = "Roberto Annunziata and Ahmad Kheirkhah and Pedram Hamrah and Emanuele Trucco",

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Annunziata, R, Kheirkhah, A, Hamrah, P & Trucco, E 2015, Scale and curvature invariant ridge detector for tortuous and fragmented structures. in N Navab, J Hornegger, WM Wells & AF Frangi (eds), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III. Lecture notes in computer science, vol. 9351, Springer International Publishing, pp. 588-595, 18th International Conference on Medical Image Computing and Computer Assisted Interventions, Munich, Germany, 5/10/15. https://doi.org/10.1007/978-3-319-24574-4_70

Scale and curvature invariant ridge detector for tortuous and fragmented structures. / Annunziata, Roberto (Lead / Corresponding author); Kheirkhah, Ahmad; Hamrah, Pedram et al.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III. ed. / Nassir Navab; Joachim Hornegger; William M. Wells; Alejandro F. Frangi . Springer International Publishing, 2015. p. 588-595 (Lecture notes in computer science; Vol. 9351).

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

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T1 - Scale and curvature invariant ridge detector for tortuous and fragmented structures

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AU - Kheirkhah, Ahmad

AU - Hamrah, Pedram

AU - Trucco, Emanuele

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N2 - Segmenting dendritic trees and corneal nerve fibres is challenging due to their uneven and irregular appearance in the respective image modalities. State-of-the-art approaches use hand-crafted features based on local assumptions that are often violated by tortuous and point-like structures, e.g., straight tubular shape. We propose a novel ridge detector, SCIRD, which is simultaneously rotation, scale and curvature invariant, and relaxes shape assumptions to achieve enhancement of target image structures. Experimental results on three datasets show that our approach outperforms state-of-the-art hand-crafted methods on tortuous and point-like structures, especially when captured at low resolution or limited signal-to-noise ratio and in the presence of other non-target structures.

AB - Segmenting dendritic trees and corneal nerve fibres is challenging due to their uneven and irregular appearance in the respective image modalities. State-of-the-art approaches use hand-crafted features based on local assumptions that are often violated by tortuous and point-like structures, e.g., straight tubular shape. We propose a novel ridge detector, SCIRD, which is simultaneously rotation, scale and curvature invariant, and relaxes shape assumptions to achieve enhancement of target image structures. Experimental results on three datasets show that our approach outperforms state-of-the-art hand-crafted methods on tortuous and point-like structures, especially when captured at low resolution or limited signal-to-noise ratio and in the presence of other non-target structures.

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SP - 588

EP - 595

BT - Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015

A2 - Navab, Nassir

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ER -

Annunziata R, Kheirkhah A, Hamrah P, Trucco E. Scale and curvature invariant ridge detector for tortuous and fragmented structures. In Navab N, Hornegger J, Wells WM, Frangi AF, editors, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III. Springer International Publishing. 2015. p. 588-595. (Lecture notes in computer science). doi: 10.1007/978-3-319-24574-4_70

Scale and curvature invariant ridge detector for tortuous and fragmented structures

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