Logo
  • Home
  • About Us
    • Aim and Scope
    • Research Area
    • Impact Factor
    • Indexing
  • For Authors
    • Authors Guidelines
    • How to publish paper?
    • Download Paper format
    • Submit Manuscript
    • Processing Charges
    • Download Copyrights Form
    • Submit Payment-Copyrights
  • Archives
    • Current Issues
    • Past Issues
    • Conference Issues
    • Special Issues
    • Advance Search
  • IJARIIE Board
    • Join as IJARIIE Board
    • Advisory Board
    • Editorial Board
    • Sr. Reviewer Board
    • Jr. Reviewer Board
  • Proposal
    • Conferece Proposal
    • Special Proposal
    • Faqs
  • Contact Us
  • Payment Detail

Call for Papers:Vol.11 Issue.3

Submission
Last date
28-Jun-2025
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-11,Issue-3. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

  • How to Publish Paper
  • Submit Manuscript
  • Processing Charges
  • Submit Payment

Archives

  • Current Issue
  • Past Issue

IJARIIE Board

  • Member Of Board
  • Join As Board

Downloads

  • Authors Guidelines
  • Manuscript Template
  • Copyrights Form

Android App

Download IJARIIE APP
  • Authors
  • Abstract
  • Citations
  • Downloads
  • Similar-Paper

Authors

Title: :  Automated unsupervised recognition of cone photoreceptor cells in adaptive optics scanning laser ophthalmoscope images
PaperId: :  24881
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 4 2024
DUI:    16.0415/IJARIIE-24881
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
RakeshSunrise University
Dr. Puru NaikSunrise University

Abstract

Physics
Cone photoreceptor cells, Laser, ophthalmoscope images
Identifying the specific type of cell, known as the cone photoreceptor cell, is essential for accurately diagnosing and treating many eye diseases. This research presents a novel automated approach that use unsupervised learning to detect CPCs in images obtained from adaptive optics scanning laser ophthalmoscopes. This approach is founded on the fundamental concepts of machine learning. The steps involved in this approach include of estimating CPC numbers, rectifying bias fields, autonomously recognizing CPCs, and integrating data from nearby sites during CPC identification. This procedure is done sequentially. The results of our study demonstrated that the proposed method surpassed the manually created techniques in terms of recall (84.4%), accuracy (92.9%), and F1 score (88.4%). Based on the results of this comparison, the proposed approach demonstrated satisfactory performance. Our approach is capable of processing AO-SLO images of both normal and diseased retinas, including those with different CPC densities, as well as images of diabetic retinopathy. The findings demonstrated the high precision of our approach in identifying circulating progenitor cells (CPCs) in eye tissue samples from both healthy individuals and those with diabetic retinopathy.The objective of this project is to create a completely automated and unsupervised method for identifying cone photoreceptor cells in AOSLO (Adaptive Optics Scanning Laser Ophthalmoscope) images. An exhaustive examination of cone photoreceptors can offer valuable understanding into numerous retinal illnesses; these cells are essential for vision. These cells are famously challenging to detect using standard approaches due to their high degree of physical interaction and effort required. The objective of this project is to develop an innovative approach that utilizes cutting-edge machine learning algorithms to detect and classify cone cells in AOSLO images, without requiring pre-existing labeled training data. The program employs image processing techniques and feature extraction algorithms to differentiate cone cells based on their distinct structural attributes. The objective of this study is to mechanize the process of identifying retinal images in order to enhance efficiency and precision. This has the capacity to improve both the diagnostic capacities and the monitoring of therapy for retinal illnesses.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Rakesh, and Dr. Puru Naik. "Automated unsupervised recognition of cone photoreceptor cells in adaptive optics scanning laser ophthalmoscope images" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 4 2024 Page 3363-3372
MLA Rakesh, and Dr. Puru Naik. "Automated unsupervised recognition of cone photoreceptor cells in adaptive optics scanning laser ophthalmoscope images." International Journal Of Advance Research And Innovative Ideas In Education 10.4(2024) : 3363-3372.
APA Rakesh, & Dr. Puru Naik. (2024). Automated unsupervised recognition of cone photoreceptor cells in adaptive optics scanning laser ophthalmoscope images. International Journal Of Advance Research And Innovative Ideas In Education, 10(4), 3363-3372.
Chicago Rakesh, and Dr. Puru Naik. "Automated unsupervised recognition of cone photoreceptor cells in adaptive optics scanning laser ophthalmoscope images." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 4 (2024) : 3363-3372.
Oxford Rakesh, and Dr. Puru Naik. 'Automated unsupervised recognition of cone photoreceptor cells in adaptive optics scanning laser ophthalmoscope images', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 4, 2024, p. 3363-3372. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Automated_unsupervised_recognition_of_cone_photoreceptor_cells_in_adaptive_optics_scanning_laser_ophthalmoscope_images_ijariie24881.pdf (Accessed : ).
Harvard Rakesh, and Dr. Puru Naik. (2024) 'Automated unsupervised recognition of cone photoreceptor cells in adaptive optics scanning laser ophthalmoscope images', International Journal Of Advance Research And Innovative Ideas In Education, 10(4), pp. 3363-3372IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Automated_unsupervised_recognition_of_cone_photoreceptor_cells_in_adaptive_optics_scanning_laser_ophthalmoscope_images_ijariie24881.pdf (Accessed : )
IEEE Rakesh, and Dr. Puru Naik, "Automated unsupervised recognition of cone photoreceptor cells in adaptive optics scanning laser ophthalmoscope images," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 4, pp. 3363-3372, Jul-Aug 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/Automated_unsupervised_recognition_of_cone_photoreceptor_cells_in_adaptive_optics_scanning_laser_ophthalmoscope_images_ijariie24881.pdf [Accessed : ].
Turabian Rakesh, and Dr. Puru Naik. "Automated unsupervised recognition of cone photoreceptor cells in adaptive optics scanning laser ophthalmoscope images." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 4 ().
Vancouver Rakesh, and Dr. Puru Naik. Automated unsupervised recognition of cone photoreceptor cells in adaptive optics scanning laser ophthalmoscope images. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : ]; 10(4) : 3363-3372. Available from: https://ijariie.com/AdminUploadPdf/Automated_unsupervised_recognition_of_cone_photoreceptor_cells_in_adaptive_optics_scanning_laser_ophthalmoscope_images_ijariie24881.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
Teaching and learning process to enhance teaching effectivenessComputer EngineringProf: Patare Rajendra Abasaheb Download
Emerging Trends in Renewable Energy: Innovations and Future Directions for Solar, Wind, and Geothermal PowerPhysicsEnass Milud Shaban Algammudi Download
Global Renewable Energy Utilization: A Five-Year Review (2019-2024)Renewable EnergyB. M. Pehere Download
THE FUTURE OF SPACE EXPLORATION: PHYSICS CHALLENGES AHEADPhysics SUNEET SINGH Download
Revolutionizing Technology: Exploring The Applications of Quantum Physics In Computing, Communication, And Advanced MaterialsPhysicsKammili Sirisha Download
Review On Natural Hybrid Composite MaterialsEngineeringNithin M Download
Preparation, characterization and antimicrobial potential of essential oil based nano emulsion formulated with Saponin extractBio PhysicsMiss. Jaya Nalawade Download
EXPLORING THE RECENT ADVANCEMENT OF HIGH TEMPERATURE SUPERCONDUCTORSScienceS V Sharma Download
ASTRAL PROJECTIONPhysicsJ. P. Pramod Download
Exploring the Applications of High Temperature Superconductors in Modern TechnologiesScienceS V Sharma Download
Methodology to Size a Hybrid Energy Systems for Remote Regions: Technical-economic Analysis, Minimizing LCoE and CO2 EmissionsSciences and TechnologiesF. Philibert ANDRINIRINIAIMALAZA Download
Automated unsupervised recognition of cone photoreceptor cells in adaptive optics scanning laser ophthalmoscope imagesPhysicsRakesh Download
FLUID MECHANICS IN ACTION: THE FUTURE OF THAI BRIDGES WITH HYDRAULIC TECHNOLOGYCivil EngineeringAmie G. Jara Download
THE HIGGS BOSON DISCOVERY: IMPLICATIONS FOR PARTICLE PHYSICSPhysics Sahil Kumar Download
GRAVITATIONAL WAVES: OBSERVATIONAL EVIDENCE AND IMPLICATIONS FOR ASTROPHYSICSPhysics Sahil Kumar Download
12
For Authors
  • Submit Paper
  • Processing Charges
  • Submit Payment
Archive
  • Current Issue
  • Past Issue
IJARIIE Board
  • Member Of Board
  • Join As Board
Privacy and Policy
Follow us

Contact Info
  • +91-8401209201 (India)
  • +86-15636082010 (China)
  • ijariiejournal@gmail.com
  • M-20/234 Ami Appt,
    Nr.Naranpura Tele-Exch,
    Naranpura,
    Ahemdabad-380063
    Gujarat,India.
Copyright © 2025. IJARIIE. All Rights Reserved.