Prediction and Therapeutic Design for Diabetic Retinopathy Using LabVIEW

Authors

  • B. Vanmathi Assistant Professor, Arasu Engineering College, Kumbakonam, Tamil Nadu, India. Author
  • S. SubaShree UG-BioMedical Engineering, Arasu Engineering College, Kumbakonam, Tamil Nadu, India. Author
  • R. Ravanya UG-BioMedical Engineering, Arasu Engineering College, Kumbakonam, Tamil Nadu, India. Author
  • B. Vidhyavashini UG-BioMedical Engineering, Arasu Engineering College, Kumbakonam, Tamil Nadu, India. Author

DOI:

https://doi.org/10.47392/IRJAEM.2024.0059

Keywords:

LabVIEW, Chronic Hyperglycemia

Abstract

Diabetic Retinal Disease (DR) is a gradual obstruction in the functioning of the blood vessels in the retina of the eye caused by chronic hyperglycemia, which may be due to diabetes type 1 or type 2. LabVIEW software play as major role in predicting the diabetic retinopathy at different stages. The real time image of the affected eye is acquired using Vision Actuation tool in LabVIEW and then it is processed using Vision assistant tool. Lot technology is I for sending the output result to the corresponding end client. Image processing and lot. Both are implemented using LabVIEW. Additionally, the system extends its functionality beyond diagnostics by incorporating an innovative approach to monitor the temperature of the eye. By integrating LabVIEW's capabilities with lot, the proposed solution checks the temperature the eye in real-time. If the detected temperature is elevated, a Peltier crystal is employed to cool the eye, demonstrating an adaptive and responsive mechanism to address abnormal temperature conditions. Aims to check the patients whether they are suffering from diabetic retinopathy or not and if they are having the diabetic retinopathy in which stage it is. Because most diabetic people are suffering from this and may also lead to loss of vision. Due to this reason, it is highly required to classify the persons in a short time with high accuracy. Automation reduces human error and subjectivity. Can detect early stages of disease. Ability to process and analyze digital fundus images efficiently.

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Published

2024-03-18