Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Classification and Localization of Eye Diseases using CNN

Classification and Localization of Eye Diseases using CNN

Thigale, Somnath
Chavan, Tukaram
Bidarkote, Anupreeta

Paperback

Careers

ISBN10: 6207998561
ISBN13: 9786207998562
Publisher: LAP Lambert Academic Publishing
Published: Aug 13 2024
Pages: 56
Weight: 0.21
Height: 0.13 Width: 6.00 Depth: 9.00
Language: English
The most common causes of vision loss in people worldwide are cataract, glaucoma, and retinal disorders. The rising prevalence of these diseases necessitates an immediate, accurate diagnosis. The suggested approach is created and designed to make it simple for individuals to diagnose illnesses of the retina, glaucoma, cataract and many more. Artificial neural networks and convolutional neural networks are used to classify and locate eye problems. The suggested approach will reduce the amount of brought-on blindness by enabling patients to receive the necessary care for the mentioned illnesses at an early stage. The chosen method also evaluates the effectiveness and safety of cataract surgery in eyes with age-related macular degeneration in addition to identifying glaucoma and retinal diseases. This study uses photos of the fundus from healthy eyes as well as eyes with glaucoma, cataracts, and retina to show the accuracy of algorithms. Nowadays, the concept of categorizing photographs based on their fundus and extracting features is well recognized, and it also plays a crucial role in the conclusion.

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