Automatic Segmentation of Blood Vessels in Colour Retinal Images using Spatial Gabor Filter and Multiscale Analysis

P. C. Siddalingaswamy; K. Gopalakrishna Prabhu

doi:10.1007/978-3-540-92841-6_66

Automatic Segmentation of Blood Vessels in Colour Retinal Images using Spatial Gabor Filter and Multiscale Analysis

P. C. Siddalingaswamy, K. Gopalakrishna Prabhu

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

3 Citations (Scopus)

Abstract

Retinal blood vessels are significant anatomical structures in ophthalmic images. Automatic segmentation of blood vessels is one of the important steps in computer aided diagnosis system for the detection of diseases such as Diabetic Retinopathy that affect human retina. We propose a method for the segmentation of retinal blood vessels using Spatial Gabor filters as they can be tuned to the specific frequency and orientation. A new parameter is defined to facilitate filtering at different scales to detect the vessels of varying thicknesses. The method is tested on forty colour retinal images of DRIVE (Digital Retinal Images for Vessel Extraction) database with manual segmentations as ground truth. An overall accuracy of 84.22% is achieved for segmentation of retinal blood vessels.

Original language	English
Title of host publication	13th International Conference on Biomedical Engineering - ICBME 2008
Pages	274-276
Number of pages	3
Volume	23
DOIs	https://doi.org/10.1007/978-3-540-92841-6_66
Publication status	Published - 2009
Event	13th International Conference on Biomedical Engineering, ICBME 2008 - , Singapore Duration: 03-12-2008 → 06-12-2008

Conference

Conference	13th International Conference on Biomedical Engineering, ICBME 2008
Country/Territory	Singapore
Period	03-12-08 → 06-12-08

All Science Journal Classification (ASJC) codes

Biomedical Engineering
Bioengineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-540-92841-6_66

Cite this

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title = "Automatic Segmentation of Blood Vessels in Colour Retinal Images using Spatial Gabor Filter and Multiscale Analysis",

abstract = "Retinal blood vessels are significant anatomical structures in ophthalmic images. Automatic segmentation of blood vessels is one of the important steps in computer aided diagnosis system for the detection of diseases such as Diabetic Retinopathy that affect human retina. We propose a method for the segmentation of retinal blood vessels using Spatial Gabor filters as they can be tuned to the specific frequency and orientation. A new parameter is defined to facilitate filtering at different scales to detect the vessels of varying thicknesses. The method is tested on forty colour retinal images of DRIVE (Digital Retinal Images for Vessel Extraction) database with manual segmentations as ground truth. An overall accuracy of 84.22% is achieved for segmentation of retinal blood vessels.",

author = "Siddalingaswamy, {P. C.} and Prabhu, {K. Gopalakrishna}",

year = "2009",

doi = "10.1007/978-3-540-92841-6_66",

language = "English",

isbn = "9783540928409",

volume = "23",

pages = "274--276",

booktitle = "13th International Conference on Biomedical Engineering - ICBME 2008",

note = "13th International Conference on Biomedical Engineering, ICBME 2008 ; Conference date: 03-12-2008 Through 06-12-2008",

}

Siddalingaswamy, PC & Prabhu, KG 2009, Automatic Segmentation of Blood Vessels in Colour Retinal Images using Spatial Gabor Filter and Multiscale Analysis. in 13th International Conference on Biomedical Engineering - ICBME 2008. vol. 23, pp. 274-276, 13th International Conference on Biomedical Engineering, ICBME 2008, Singapore, 03-12-08. https://doi.org/10.1007/978-3-540-92841-6_66

TY - GEN

T1 - Automatic Segmentation of Blood Vessels in Colour Retinal Images using Spatial Gabor Filter and Multiscale Analysis

AU - Siddalingaswamy, P. C.

AU - Prabhu, K. Gopalakrishna

PY - 2009

Y1 - 2009

N2 - Retinal blood vessels are significant anatomical structures in ophthalmic images. Automatic segmentation of blood vessels is one of the important steps in computer aided diagnosis system for the detection of diseases such as Diabetic Retinopathy that affect human retina. We propose a method for the segmentation of retinal blood vessels using Spatial Gabor filters as they can be tuned to the specific frequency and orientation. A new parameter is defined to facilitate filtering at different scales to detect the vessels of varying thicknesses. The method is tested on forty colour retinal images of DRIVE (Digital Retinal Images for Vessel Extraction) database with manual segmentations as ground truth. An overall accuracy of 84.22% is achieved for segmentation of retinal blood vessels.

AB - Retinal blood vessels are significant anatomical structures in ophthalmic images. Automatic segmentation of blood vessels is one of the important steps in computer aided diagnosis system for the detection of diseases such as Diabetic Retinopathy that affect human retina. We propose a method for the segmentation of retinal blood vessels using Spatial Gabor filters as they can be tuned to the specific frequency and orientation. A new parameter is defined to facilitate filtering at different scales to detect the vessels of varying thicknesses. The method is tested on forty colour retinal images of DRIVE (Digital Retinal Images for Vessel Extraction) database with manual segmentations as ground truth. An overall accuracy of 84.22% is achieved for segmentation of retinal blood vessels.

UR - http://www.scopus.com/inward/record.url?scp=84891954339&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84891954339&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-92841-6_66

DO - 10.1007/978-3-540-92841-6_66

M3 - Conference contribution

AN - SCOPUS:84891954339

SN - 9783540928409

VL - 23

SP - 274

EP - 276

BT - 13th International Conference on Biomedical Engineering - ICBME 2008

T2 - 13th International Conference on Biomedical Engineering, ICBME 2008

Y2 - 3 December 2008 through 6 December 2008

ER -

Automatic Segmentation of Blood Vessels in Colour Retinal Images using Spatial Gabor Filter and Multiscale Analysis

Abstract

Conference

All Science Journal Classification (ASJC) codes

UN SDGs

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