Glaucoma Detection from Retinal Images Using Statistical and Textural Wavelet Features

Author:

Abdel-Hamid LamiaaORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference39 articles.

1. World Health Organization: Blindness and vision impairment prevention. Available at: http://www.who.int/blindness/causes/priority/en/ . Accessed May 2018.

2. Bright Focus Foundation: Glaucoma: facts & figures. Available at: https://www.brightfocus.org/glaucoma/article/glaucoma-facts-figures . Accessed May 2018.

3. Kumar BN, Chauhan RP, Dahiya N: Detection of glaucoma using image processing techniques: A critique. Semin Ophthalmol 33(2):275–228, 2018

4. Almazroa A, Burman R, Raahemifar K, Lakshminarayanan V: Optic disc and optic cup segmentation methodologies for glaucoma image detection: A survey. Journal of ophthalmology 2015:1–28, 2015

5. Kavya N, Padmaja KV: Glaucoma detection using texture features extraction. Proceedings of the 51st IEEE Asilomar Conference on Signals, Systems, and Computers, 1471–1475, 2017.

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