detection of retinal blood vessel

Presented by,Md.Mintu pk.Roll : 1209050 Dept of ECE (KUET).

Dept. of ECE ( KUET )Date : 09.08.2016 Page: 01

Automatic Detection of Blood Vessel in Retinal Images

Author,A.ELBALAOUI, M. FAKIR Faculty of Science and Technology, Sultan Moulay Slimane University Beni Mellal, Morocco.

Source: IEEE transaction on computer grapics,imaging ,and visualization. March 29 2016-April 1 2016

CONTENTS…

Page: 02

Project vision

Methodology Datasheets

Preprocesing

Vessel detection

Hessian multiscale enhancement filter

Adaptive thresholding

Result analysis

Conclusion

Dept. of ECE ( KUET )Date : 09.08.2016

PROJECT VISION..

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Detection of Blood vessel.

Measurement of vessel diameter.But why ??

For diagnosis and treatment retinal disease such as,

Diabetic Retinopathy Glaucoma Hypertensive Retinopathy


CONTINUE....

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Fig 01 : Anatomy of eye Fig 02: Fundus image of retina


CONTINUE....

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Blood Vessel Damage Precedes Vision Loss.Normal Retina Diabetic Retinopathy Hypertensive Retinopathy

Vision Loss


BLOOD VESSEL DETECTION METHOD..

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There are three parts of proposed method..

Preprocessing Retinal Image

Vesselness Filter

Hessian Multiscale Enhancement Filter

1

2

3


BLOOD VESSEL DETECTION STEPS..

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Fig 03: Block diagram of blood vessel detection method


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DATASETS..

Performance of algorithm compared three database..

DRIVE Database ( Digital Retinal Images for Vessel Extraction ) Consists of 40 color images. Images size 565×584 pixels. Spatial resolution of 20 micro/pixel.

STARE database(STructured Analysis of the Retina) Contains 81 fundus images. 31 images of healthy retinas. 50 images of retinas with disease.

CHASE_DB1 database Contains 28 color images. 14 patients in the program Child Heart. Resolution of 1280x960 pixels


PREPROCESSING METHOD..

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Fig 04: Original RGB retinal image Fig 05: Red, green, and blue histogram

Histogram


PREPROCESSING STEPS..

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Fig 06: (a) Original RGB retinal image . (b) Extract green Channel. (c) Image after CLAHE and dilate borders. (d) Enhanced image (e) zooming in rectangular region before dilate borders. (f) Zooming in rectangular region after dilated borders

DRIVE

STARE


VESSEL DETECTION STEPS....

Enhancement filtering equation :

Hessian enhancement filtering

Where

Page: 11Dept. of ECE ( KUET )Date : 09.08.2016

COMPARISON DIFFERENT STEPS FOR VESSEL ENHANCEMENT..

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Pixels

Inte

nsity

Pixels

Inte

nsity

Pixels In

tens

ity

a b

c d

Fig 07 : (a) original image, and (b) the intensity distribution of a vessel. (c)–(d) compare the enhanced performance.


RESULT ANALYSIS..

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Detection results: From DRIVE database

Fig 08 :(a) Retinal images from DRIVE database, (b) results of the proposed method, (c) the ground truth manual.

( a ) ( b ) ( c )


CONTINUE…

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Detection results: From STARE database

Fig 09 : (a) Retinal images from STARE database, (b) results of the proposed method (c) the ground truth manual.

( a ) ( b ) ( c )


CONTINUE…

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Detection results: From CHASE_DB1 database

Fig 10 : (a) Retinal images from CHASE_DB1 database, (b) the ground truth manual, (c) results of the proposed method.

( a )

( a ) ( b ) ( c )


PERFORMANCE PARAMETERS FOR PROPOSED METHOD.

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Parameter Equation Supervised method

Proposed method

Sensitivity 0.7332 0.7630

Specificity 0.9782 0.9713

Accuracy 0.9466 0.9443

Precision 0.6923 0.6835

F-measure 0.6372 0.6293


PERFORMANCE PARAMETERS..

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Fig 11 : performance evaluation for DRIVE dataset.


PERFORMANCE PARAMETERS..

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Fig 12 : performance evaluation for STARE dataset.


CONCLUSION..

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Detected retinal blood vessels .

Tested on the DRIVE, STARE and CHASE_DB1

databases.

Result higher than many of the state-of-the-art methods

Method applicable to all types of retinal images,

healthy as well as abnormal

So,Proposed Method succesfully..


REFERENCE..

[1] A.M. Mendonca and A. Campilho, “Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction,” IEEE Transactions on Medical Imaging, vol. 25, no. 9, pp. 1200-1213, 2006. [2] Ana Salazar-Gonzalez, Djibril Kaba, Yongmin Li, and Xiaohui Liu, “Segmentation of the Blood Vessels and Optic Disk in Retinal Images,” IEEE J. Biomedical and Health Informatics vol. 18, no. 6, pp. 1874-1886, 2014. [3] Leung H, Wang JJ, Rochtchina E, Wong TY, Klein R, Mitchell P (2003) Impact of current and past blood pressure on retinal arteriolar diameter in olderpopulation. J Hypertens: 1543 1549. [4] Wang JJ, Taylor B, Wong TY, Chua B, Rochtchina E, Klein R, Mitchell P (2006) Retinal vessel diameters and obesity: a population- based study in older persons. Obese Res: 206–214.

Page: 20Dept. of ECE ( KUET )Date : 09.08.2016

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Thanks for Your Attention.


detection of retinal blood vessel

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