TY - GEN
T1 - Scale and curvature invariant ridge detector for tortuous and fragmented structures
AU - Annunziata, Roberto
AU - Kheirkhah, Ahmad
AU - Hamrah, Pedram
AU - Trucco, Emanuele
N1 - Funding Information:
This research was supported by the EU Marie Curie ITN REVAMMAD, n 316990. The authors are grateful to S. McKenna, J. Zhang (CVIP, Dundee) for valuable comments and to Amos Sironi (CVlab, EPFL) for providing the VC6 and BF2D datasets. o
Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
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.
UR - http://www.scopus.com/inward/record.url?scp=84951803918&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84951803918&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-24574-4_70
DO - 10.1007/978-3-319-24574-4_70
M3 - Conference contribution
AN - SCOPUS:84951803918
SN - 9783319245737
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 588
EP - 595
BT - Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 - 18th International Conference, Proceedings
A2 - Frangi, Alejandro F.
A2 - Navab, Nassir
A2 - Hornegger, Joachim
A2 - Wells, William M.
PB - Springer Verlag
T2 - 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015
Y2 - 5 October 2015 through 9 October 2015
ER -