Isfahan University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share this content! On (X network) By
Circlet Based Framework for Optic Disk Detection Publisher



Sarrafzadeh O1 ; Rabbani H1 ; Dehnavi AM1
Authors
Show Affiliations
Authors Affiliations
  1. 1. Department of Biomedical Engineering, School of Advanced Technologies in Medicine, Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

Source: Proceedings - International Conference on Image Processing, ICIP Published:2017


Abstract

Optic Disc (OD) detection in retinal fundus images is a crucial stage for the automation of a screening system in diabetic ophthalmology. Most researches for automatic localization of OD benefit the regions of vessels. In this paper, we present a fast and novel method based on the Circlet Transform to detect OD in digital retinal fundus images that doesn't utilize the location of the vessels. First, each R, G and B band is enhanced using CLAHE method. Then, the enhanced image in RGB color space is converted to L-a-b one. Next, the Circlet transform is applied to the L- band, and finally, the Circlet transform coefficients are analyzed to find the location of the OD. The proposed algorithm is implemented on DRIVE dataset and the experimental results show a very well OD localization. The correct rate of the proposed method is 95% even though it doesn't utilize the vessels' structure. © 2017 IEEE.
Related Docs
View other Related Docs
1. Automatic Detection of the Optic Disc of the Retina: A Fast Method, Journal of Medical Signals and Sensors (2016)
2. Automatic Optic Disk Boundary Extraction by the Use of Curvelet Transform and Deformable Variational Level Set Model, Pattern Recognition (2012)
3. Analysis of Fundus Fluorescein Angiogram Based on the Hessian Matrix of Directional Curvelet Sub-Bands and Distance Regularized Level Set Evolution, Journal of Medical Signals and Sensors (2015)
4. Automatic Optic Disk Detection by the Use of Curvelet Transform, Final Program and Abstract Book - 9th International Conference on Information Technology and Applications in Biomedicine, ITAB 2009 (2009)
5. A New Method for the Localization of Hard Exudates Based on Analyzing Intensity Incremental-Decremental Trends, IEEE Transactions on Instrumentation and Measurement (2024)
6. A New Combined Method Based on Curvelet Transform and Morphological Operators for Automatic Detection of Foveal Avascular Zone, Signal, Image and Video Processing (2014)
7. Exudate Identification in Retinal Fundus Images Using Precise Textural Verifications, Scientific Reports (2023)
8. Automatic Brain Aneurysm Extraction in Angiography Videos Using Circlet Transform and a Modified Level Set Model, Current Medical Imaging Reviews (2018)
Experts (# of related papers)
View all Related Experts
Hossein Rabbani (30)
Alireza Mehri-Dehnavi (8)
Other Related Docs
9. Automatic Detection of Exudates and Optic Disk in Retinal Images Using Curvelet Transform, IET Image Processing (2012)
10. Analysis of Foveal Avascular Zone for Grading of Diabetic Retinopathy Severity Based on Curvelet Transform, Graefe's Archive for Clinical and Experimental Ophthalmology (2012)
11. Evaluation of Asymmetry in Right and Left Eyes of Normal Individuals Using Extracted Features From Optical Coherence Tomography and Fundus Images, Journal of Medical Signals and Sensors (2021)
12. Fully Automatic Segmentation of Fluorescein Leakage in Subjects With Diabetic Macular Edema, Investigative Ophthalmology and Visual Science (2015)
13. Diabetic Retinopathy Detection in Ocular Imaging by Dictionary Learning, Diabetes and Fundus OCT (2020)
14. Vessel Centerlines Extraction From Fundus Fluorescein Angiogram Based on Hessian Analysis of Directional Curvelet Subbands, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (2013)
15. Registration of Optical Coherence Tomography (Oct) of Optic Nerve Head and Fundus Images Using Speeded-Up Robust Features (Surf) and Random Sample Consensus (Ransac) Algorithms, Journal of Isfahan Medical School (2016)
16. The Ellipselet Transform, Journal of Medical Signals and Sensors (2019)
17. A Computationally Efficient Red-Lesion Extraction Method for Retinal Fundus Images, IEEE Transactions on Instrumentation and Measurement (2023)
18. Detecting Red-Lesions From Retinal Fundus Images Using Unique Morphological Features, Scientific Reports (2023)
19. Exact Localization of Breakpoints of Retinal Pigment Epithelium in Optical Coherence Tomography of Optic Nerve Head, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (2017)
20. Hybrid Registration of Retinal Fluorescein Angiography and Optical Coherence Tomography Images of Patients With Diabetic Retinopathy, Biomedical Optics Express (2021)
21. Registration of Fluorescein Angiography and Optical Coherence Tomography Images of Curved Retina Via Scanning Laser Ophthalmoscopy Photographs, Biomedical Optics Express (2020)
22. A Comprehensive Study of Retinal Vessel Classification Methods in Fundus Images, Journal of Medical Signals and Sensors (2017)
23. Offline Handwritten Signature Verification Based on Circlet Transform and Statistical Features, Iranian Conference on Machine Vision and Image Processing, MVIP (2020)
24. Red-Lesion Extraction in Retinal Fundus Images by Directional Intensity Changes’ Analysis, Scientific Reports (2021)
25. A Device-Independent, Shape Preserving Retinal Optical Coherence Tomography Image Alignment Method Applying Tv-Unet for Rpe Layer Detection, IEEE Transactions on Instrumentation and Measurement (2022)
26. Automatic Detection of Microaneurysms in Oct Images Using Bag of Features, Computational and Mathematical Methods in Medicine (2022)
27. Local Comparison of Cup to Disc Ratio in Right and Left Eyes Based on Fusion of Color Fundus Images and Oct B-Scans, Information Fusion (2019)
28. Detection and Registration of Vessels of Fundus and Oct Images Using Curevelet Analysis, IEEE 12th International Conference on BioInformatics and BioEngineering, BIBE 2012 (2012)
29. A New Curvelet Transform Based Method for Extraction of Red Lesions in Digital Color Retinal Images, Proceedings - International Conference on Image Processing, ICIP (2010)
30. Diabetic Retinopathy Grading by Digital Curvelet Transform, Computational and Mathematical Methods in Medicine (2012)