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Adaptive local thresholding by verification-based multithreshold probing with application to vessel detection in retinal images
Abstract
In this paper, we propose a general framework of adaptive local thresholding based on a verification-based multithreshold probing scheme. Object hypotheses are generated by binarization using hypothetic thresholds and accepted/rejected by a verification procedure. The application-dependent verification procedure can be designed to fully utilize all relevant informations about the objects of interest. In this sense, our approach is regarded as knowledge-guided adaptive thresholding, in contrast to most algorithms known from the literature. We apply our general framework to detect vessels in retinal images. An experimental evaluation demonstrates superior performance over global thresholding and a vessel detection method recently reported in the literature. Due to its simplicity and general nature, our novel approach is expected to be applicable to a variety of other applications.
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Cited by
Ridge-based vessel segmentation in color images of the retina
Staal, J., Abramoff, M. D., Niemeijer, M., Viergever, M. A., & van Ginneken, B. (2004) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2004.825627 · Cited by 4,202
Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification
Soares, J. V. B., Leandro, J. J. G., Cesar, R. M., Jelinek, H. F., & Cree, M. J. (2006) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2006.879967 · Cited by 1,497
Marín, D., Aquino, A., Gegundez-Arias, M. E., & Bravo, J. M. (2011) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2010.2064333 · Cited by 929
Segmenting Retinal Blood Vessels WithDeep Neural Networks
Liskowski, P., & Krawiec, K. (2016) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2016.2546227 · Cited by 890
Retinal Blood Vessel Segmentation Using Line Operators and Support Vector Classification
Ricci, E., & Perfetti, R. (2007) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2007.898551 · Cited by 818
Metadata
- Authors
- Jiang, X., & Mojon, D.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2003-01
- Volume
- 25
- Issue
- 1
- Pages
- 131-137
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2115680416
- Cited by
- 679
- References
- 0
- FWCI
- 10.60
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jiang, X., & Mojon, D. (2003). Adaptive local thresholding by verification-based multithreshold probing with application to vessel detection in retinal images. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2003.1159954
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