Automatic Analysis of Color Fundus Photographs and Its Application to the Diagnosis of Diabetic Retinopathy

Walter, Thomas; Klein, Jean-Claude

doi:10.1007/0-306-48606-7_7

Cited by 19 publications

(12 citation statements)

References 16 publications

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“…In this subsection, we want to make a few remarks on this observation; a more detailed discussion can be found in Walter and Klein (2005) and Moreno Barriuso (2000).…”

Section: Use Of Color Informationmentioning

confidence: 95%

Automatic detection of microaneurysms in color fundus images

Walter¹,

Massin

Erginay

et al. 2007

Medical Image Analysis

Self Cite

311

133

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“…In this subsection, we want to make a few remarks on this observation; a more detailed discussion can be found in Walter and Klein (2005) and Moreno Barriuso (2000).…”

Section: Use Of Color Informationmentioning

confidence: 95%

Automatic detection of microaneurysms in color fundus images

Walter¹,

Massin

Erginay

et al. 2007

Medical Image Analysis

Self Cite

311

133

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“…Although it is known that the green channel of an RGB retinography is the one with highest contrast [32], upon observing the imagery it was revealed that when the fovea is visible in the colour image it is also often present in the red channel. Therefore, the processing described in this section is performed in parallel on the red and green components and the "better" of the two results is ultimately selected.…”

Section: Obtaining Accurate Fovea Centre Locationmentioning

confidence: 99%

Establishing the macular grading grid by means of fovea centre detection using anatomical-based and visual-based features

Aquino

2014

Computers in Biology and Medicine

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“…Hoover and Goldbaum [5]. Finding the OD can be used to decrease false positives in the detection of regions of retinal exudates [7]. These injuries are a diagnostic key to grading the risk of macular edema.…”

Section: Overview Of Papermentioning

confidence: 99%

To Find Location of Optic Disc in Digital Fundus Images

Mane¹,

Kale²

2017

International Advanced Research Journal in Science, Engineering

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Optic disc (OD) location plays an important role in automatic diagnosis of diabetic retinopathy. Medical image analysis and processing has great significance in the field of medicine, especially in non-invasive treatment and clinical study. Changes in optic disc shape and area may indicate disease processes, particularly glaucoma, and accurate identification of the disk boundary may be used to quantify changes. In this paper we are presenting the preprocessing step which will be beneficial further to calculate the cup to boundary ratio of optic disc. This paper presents technique for finding location of optic disc from digital retinal image. The optic disc pixel (ODP) should first determine for further processing. The optic disc pixel (ODP) can be further used for finding location of optic disc. Three methodologies for finding optic disc pixel and finally one voting algorithm for final optic disc pixel are presented in this paper.Keywords: optic disc pixel (ODP), maximum variance method, maximum difference method, low pass filter method.

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Automatic Analysis of Color Fundus Photographs and Its Application to the Diagnosis of Diabetic Retinopathy

Cited by 19 publications

References 16 publications

Automatic detection of microaneurysms in color fundus images

Automatic detection of microaneurysms in color fundus images

Establishing the macular grading grid by means of fovea centre detection using anatomical-based and visual-based features

To Find Location of Optic Disc in Digital Fundus Images

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