Novel method for automatic generation of fundus mask

Santhakumar, R.; Rajkumar, E; Tandur, Megha; Geetha, K.; Rajamani, Kumar; Haritz, Girish

doi:10.1109/iciip.2015.7414756

Cited by 3 publications

(1 citation statement)

References 6 publications

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“…Amruthavarshini et al [7] has used extracted features and migraph classifier to segment the optic disc. Santhakumar et al [8] has created a perfect mask for segmenting the foreground in the fundus image. The author has used logarithmic transformation along with Otsu's thresholding to segment and further used morphological operation to close.…”

Section: Optic Disk Detectionmentioning

confidence: 99%

Robust CDR calculation for glaucoma identification

Kurian¹,

Rs²

2018

biomedicalresearch

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The two major eye diseases that affect human eye is Glaucoma and Diabetic retinopathy. Both these diseases cause permanent eye damage and about 50% of vision loss before identification. Till date early detection of these vision loss causing diseases is challenging. These diseases can be identified only after it has damaged more than 25% of the eye. Glaucoma is caused due to increase in the intraocular pressure that damages the retinal. The inner side of the retina is viewed through a camera called the Fundus Imager. This imager is capable of recording the view of retina with respect to the patient. This procedure makes us capable to identify the damages caused by these diseases in early stages. Detecting the optic disc and cup from a fundus image and calculating the CDR value is a method used to identify glaucoma in its early stages. In this paper we have proposed an automatic process to locate the optic disc and the optic cup from the retinal image. The optic disc is located at the centre of the eyes nervous system. This is the brightest region of the fundus image. The cup which is the inner part of the optic disc is obtained by further segmenting the fundus image. For better results different color planes of the same fundus image is been used. The optic cup to disc ratio is an important factor used to identify glaucoma. Glaucoma patients have a high CDR value. This is mainly due to the increase in the cup diameter. This can also be related to the thinning of the nerve rim.

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Section: Optic Disk Detectionmentioning

confidence: 99%

Robust CDR calculation for glaucoma identification

Kurian¹,

Rs²

2018

biomedicalresearch

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A Universal Field-of-View Mask Segmentation Method on Retinal Images From Fundus Cameras

Starovoitov,

Son,

Golub

et al. 2024

IEEE Access

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Review of Preprocessing Techniques for Fundus Image Analysis

Joshi¹,

Karule²

2017

AMA_B

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The principal target of preprocessing is to get more appropriate resultant image than its original for further additional analysis. Enhancement of retinal images creates several challenges. The main obstacle is to develop a technique to accommodate the wide variation in contrast inside the image. Necessity of preprocessing methods are for image normalization and to increase the contrast for achieving accurate analysis. This work examined literature in the prior process of digital imaging, in the field of the analysis of fundus image to extract normal and pathologic retinal traits within the context of diabetic retinopathy (DR).

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Novel method for automatic generation of fundus mask

Cited by 3 publications

References 6 publications

Robust CDR calculation for glaucoma identification

Robust CDR calculation for glaucoma identification

A Universal Field-of-View Mask Segmentation Method on Retinal Images From Fundus Cameras

Review of Preprocessing Techniques for Fundus Image Analysis

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