Machine Learning

Detection of glaucoma

Glaucoma is a serious disease which left untreated can lead to permanent and irreversible blindness. The main problem with these types of retinal damage is that its symptoms are not seen in initial stages

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The other issue is that there will be no initial pain.

The advanced stages of glaucoma show effect such as thinness of the cornea, high eye pressure, and abnormal optic nerve anatomy.

The human eye produces fluid which provides nutrition to the eye. But when the eye's drainage system is blocked eye produces an excess of fluid that leads to an imbalance in the fluid flow

Now the various structure of the retina and various symptoms are discussed

Structure of retina

  1. Optic disc: The nerves that enter into the round regions of the retina
  2. Fovea: This is a part of an eye which contains only cones and helps in accurate vision
  3. Macula: The portion in the middle of the retina which helps in seeing the objects
  4. Anterior chamber: the chamber which is filled with a fluid called aqueous humor

Symptoms of Glaucoma

  1. The vision of the eye is gradually lost, which affects both the eyes
  2. The person with this disease will be having tunneled vision
  3. The person with this disease will be having blurred vision
  4. The person with this disease will be having red eyes

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Glaucoma detection procedure

  1. The retinal images are initially captured using digital devices
  2. When the above procedure is completed then glaucoma detection process is started
  3. Now the images are pre-processed so that they can be equalized and reshaped then the irregularities in the image can be removed
  4. Now Feature extraction process is performed so that the large data set can be described precisely
  5. The methods which are used in feature extraction are Pixel intensity values, textures, Histogram model, etc.
  6. Now the image classification is performed which analyses the images numerical properties and organizes the data of the image
  7. The above steps are performed accurately such that accurate results are obtained
  8. Now the results which are attained for a set of data is used to check whether the image of the retina is normal or glaucomatous

Various methods to detect Glaucoma

  1. Using wavelet features of the segmented optic disc from fundus image
  2. Detection using CDR (cup to disc ratio)
  3. Super pixel classification technique for glaucoma screening.
  4. Using PCA and mathematical morphology
  5. Using Texture and Higher-Order Spectra Features
  6. Detection of glaucoma without segmentation


Hence it can be concluded that with the above methods the Glaucoma can be detected and preventive measures can be taken to avoid glaucoma.

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Detection of glaucoma
Skyfi Labs Last Updated: 2022-03-19

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