An enhanced segmentation of blood vessels in retinal images using Contourlet

S. H. Rezatofighi; A. Roodaki; H. Ahmadi Noubari

doi:10.1109/iembs.2008.4649967

An enhanced segmentation of blood vessels in retinal images using Contourlet

S. H. Rezatofighi
, A. Roodaki
, H. Ahmadi Noubari

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

12 Citations (Scopus)

Abstract

Retinal images acquired using a fund us camera often contain low grey, low level contrast and are of low dynamic range. This may seriously affect the automatic segmentation stage and subsequent results; hence, it is necessary to carry-out preprocessing to improve image contrast results before segmentation. Here we present a new multi-scale method for retinal image contrast enhancement using Contourlet transform. In this paper, a combination of feature extraction approach which utilizes Local Binary Pattern (LBP), morphological method and spatial image processing is proposed for segmenting the retinal blood vessels in optic fundus images. Furthermore, performance of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multilayer Perceptron (MLP) is investigated in the classification section. The performance of the proposed algorithm is tested on the publicly available DRIVE database. The results are numerically assessed for different proposed algorithms.

Original language	English
Title of host publication	Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	3530-3533
Number of pages	4
ISBN (Print)	9781424418152
DOIs	https://doi.org/10.1109/iembs.2008.4649967
Publication status	Published - 14 Oct 2008
Externally published	Yes
Event	International Conference of the IEEE Engineering in Medicine and Biology Society 2008 - Vancouver Convention and Exhibition Centre, Vancouver, Canada Duration: 20 Aug 2008 → 25 Aug 2008 Conference number: 30th https://ieeexplore.ieee.org/xpl/conhome/4636107/proceeding (Proceedings)

Conference

Conference	International Conference of the IEEE Engineering in Medicine and Biology Society 2008
Abbreviated title	EMBC 2008
Country/Territory	Canada
City	Vancouver
Period	20/08/08 → 25/08/08
Internet address	https://ieeexplore.ieee.org/xpl/conhome/4636107/proceeding (Proceedings)

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10.1109/iembs.2008.4649967

Cite this

Rezatofighi, S. H., Roodaki, A., & Noubari, H. A. (2008). An enhanced segmentation of blood vessels in retinal images using Contourlet. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 (pp. 3530-3533). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/iembs.2008.4649967

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title = "An enhanced segmentation of blood vessels in retinal images using Contourlet",

abstract = "Retinal images acquired using a fund us camera often contain low grey, low level contrast and are of low dynamic range. This may seriously affect the automatic segmentation stage and subsequent results; hence, it is necessary to carry-out preprocessing to improve image contrast results before segmentation. Here we present a new multi-scale method for retinal image contrast enhancement using Contourlet transform. In this paper, a combination of feature extraction approach which utilizes Local Binary Pattern (LBP), morphological method and spatial image processing is proposed for segmenting the retinal blood vessels in optic fundus images. Furthermore, performance of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multilayer Perceptron (MLP) is investigated in the classification section. The performance of the proposed algorithm is tested on the publicly available DRIVE database. The results are numerically assessed for different proposed algorithms.",

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year = "2008",

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doi = "10.1109/iembs.2008.4649967",

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booktitle = "Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "International Conference of the IEEE Engineering in Medicine and Biology Society 2008, EMBC 2008 ; Conference date: 20-08-2008 Through 25-08-2008",

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Rezatofighi, SH, Roodaki, A & Noubari, HA 2008, An enhanced segmentation of blood vessels in retinal images using Contourlet. in Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. IEEE, Institute of Electrical and Electronics Engineers, pp. 3530-3533, International Conference of the IEEE Engineering in Medicine and Biology Society 2008, Vancouver, British Columbia, Canada, 20/08/08. https://doi.org/10.1109/iembs.2008.4649967

An enhanced segmentation of blood vessels in retinal images using Contourlet. / Rezatofighi, S. H.; Roodaki, A.; Noubari, H. Ahmadi.
Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. IEEE, Institute of Electrical and Electronics Engineers, 2008. p. 3530-3533.

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

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AB - Retinal images acquired using a fund us camera often contain low grey, low level contrast and are of low dynamic range. This may seriously affect the automatic segmentation stage and subsequent results; hence, it is necessary to carry-out preprocessing to improve image contrast results before segmentation. Here we present a new multi-scale method for retinal image contrast enhancement using Contourlet transform. In this paper, a combination of feature extraction approach which utilizes Local Binary Pattern (LBP), morphological method and spatial image processing is proposed for segmenting the retinal blood vessels in optic fundus images. Furthermore, performance of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multilayer Perceptron (MLP) is investigated in the classification section. The performance of the proposed algorithm is tested on the publicly available DRIVE database. The results are numerically assessed for different proposed algorithms.

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BT - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08

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ER -

An enhanced segmentation of blood vessels in retinal images using Contourlet

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