CNN Based Retinal Micro Aneurysm Detection With Multi-Sieving Deep Learing using Thermal Images

Authors

  • Pratibha Aghav Student ,Dept. Of Computer Engineering, PKTC PUNE , Maharashtra, India
  • Ankita Medankar Student ,Dept. Of Computer Engineering, PKTC PUNE , Maharashtra, India
  • Suhasini Nalawade Student ,Dept. Of Computer Engineering, PKTC PUNE , Maharashtra, India
  • Prof. V.N.Dhage Student ,Dept. Of Computer Engineering, PKTC PUNE , Maharashtra, India

Keywords:

Diabetic Retinopathy, Infrared Thermography, CNN

Abstract

Diabetic Retinopathy is one of the serious issues around the world. That can make significant debilitation the
eyes, including a lasting loss of vision. Early discovery of eye maladies builds the endurance rate by effective treatment.
The proposed approach is to investigate AI system to distinguish DR utilizing Thermography pictures of an eye and to
present the impact of warm variety of variation from the norm in the eye structure as a finding imaging methodology
which are valuable for ophthalmologists to do the clinical determination. Warm pictures are pre-handled, and dependent
on surface highlights from dark pictures, factual highlights from RGB and HSI pictures are extricated and arranged
utilizing classifier with different blend of highlights. After that we utilize the pictures to our CNN classifier model and
recognize the Diabetic Retinopathy.

Downloads

Published

2019-12-25

How to Cite

Pratibha Aghav, Ankita Medankar, Suhasini Nalawade, & Prof. V.N.Dhage. (2019). CNN Based Retinal Micro Aneurysm Detection With Multi-Sieving Deep Learing using Thermal Images. International Journal of Advance Research in Engineering, Science & Technology, 6(12), 12–15. Retrieved from https://ijarest.org/index.php/ijarest/article/view/1964

Issue

Vol. 6 No. 12 (2019): Volume: 06, Issue: 12 - December, 2019.

Section

Articles