2-D Empirical LP Wavelet Transform based Automated Framework for Glaucoma Screening

Deepak Parashar; Om Mishra; Kanhaiya Sharma; Shilpa Choudhary

doi:10.1109/ICDT57929.2023.10151239

2-D Empirical LP Wavelet Transform based Automated Framework for Glaucoma Screening

Deepak Parashar^*
, Om Mishra
, Kanhaiya Sharma
, Shilpa Choudhary

^*Corresponding author for this work

School of Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Glaucoma is a severe condition that causes eyesight loss. The ability to recognize glaucoma in its early stages is critical in preventing long-term vision loss. This paper presents a two-dimensional empirical Littlewood - Paley (LP) wavelet transform (2D-EWT)-based method for glaucoma detection using retinal fundus pictures. For the decay of the preanalyzed photographs into different sub-bands, EWT is used in this investigation. High-frequency sub-band images are then used to compute the features. The ReliefF method chose the valuable descriptors from the extricated include set. Finally, selected descriptors are classified using the random forest (RF) classifier. We use the RIM-ONE public online glaucoma database for performance evaluation of the proposed framework.

Original language	English
Title of host publication	2023 International Conference on Disruptive Technologies, ICDT 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	695-697
Number of pages	3
ISBN (Electronic)	9798350323887
DOIs	https://doi.org/10.1109/ICDT57929.2023.10151239
Publication status	Published - 2023
Event	2023 International Conference on Disruptive Technologies, ICDT 2023 - Greater Noida, India Duration: 11-05-2023 → 12-05-2023

Publication series

Name	2023 International Conference on Disruptive Technologies, ICDT 2023

Conference

Conference	2023 International Conference on Disruptive Technologies, ICDT 2023
Country/Territory	India
City	Greater Noida
Period	11-05-23 → 12-05-23

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Control and Optimization
Computer Networks and Communications
Computer Science Applications
Computer Vision and Pattern Recognition
Information Systems
Information Systems and Management
Safety, Risk, Reliability and Quality

Access to Document

10.1109/ICDT57929.2023.10151239

Cite this

Parashar, D., Mishra, O., Sharma, K., & Choudhary, S. (2023). 2-D Empirical LP Wavelet Transform based Automated Framework for Glaucoma Screening. In 2023 International Conference on Disruptive Technologies, ICDT 2023 (pp. 695-697). (2023 International Conference on Disruptive Technologies, ICDT 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDT57929.2023.10151239

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title = "2-D Empirical LP Wavelet Transform based Automated Framework for Glaucoma Screening",

abstract = "Glaucoma is a severe condition that causes eyesight loss. The ability to recognize glaucoma in its early stages is critical in preventing long-term vision loss. This paper presents a two-dimensional empirical Littlewood - Paley (LP) wavelet transform (2D-EWT)-based method for glaucoma detection using retinal fundus pictures. For the decay of the preanalyzed photographs into different sub-bands, EWT is used in this investigation. High-frequency sub-band images are then used to compute the features. The ReliefF method chose the valuable descriptors from the extricated include set. Finally, selected descriptors are classified using the random forest (RF) classifier. We use the RIM-ONE public online glaucoma database for performance evaluation of the proposed framework.",

author = "Deepak Parashar and Om Mishra and Kanhaiya Sharma and Shilpa Choudhary",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 International Conference on Disruptive Technologies, ICDT 2023 ; Conference date: 11-05-2023 Through 12-05-2023",

year = "2023",

doi = "10.1109/ICDT57929.2023.10151239",

language = "English",

series = "2023 International Conference on Disruptive Technologies, ICDT 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Parashar, D, Mishra, O, Sharma, K & Choudhary, S 2023, 2-D Empirical LP Wavelet Transform based Automated Framework for Glaucoma Screening. in 2023 International Conference on Disruptive Technologies, ICDT 2023. 2023 International Conference on Disruptive Technologies, ICDT 2023, Institute of Electrical and Electronics Engineers Inc., pp. 695-697, 2023 International Conference on Disruptive Technologies, ICDT 2023, Greater Noida, India, 11-05-23. https://doi.org/10.1109/ICDT57929.2023.10151239

2-D Empirical LP Wavelet Transform based Automated Framework for Glaucoma Screening. / Parashar, Deepak; Mishra, Om; Sharma, Kanhaiya et al.
2023 International Conference on Disruptive Technologies, ICDT 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 695-697 (2023 International Conference on Disruptive Technologies, ICDT 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - 2-D Empirical LP Wavelet Transform based Automated Framework for Glaucoma Screening

AU - Parashar, Deepak

AU - Mishra, Om

AU - Sharma, Kanhaiya

AU - Choudhary, Shilpa

PY - 2023

Y1 - 2023

N2 - Glaucoma is a severe condition that causes eyesight loss. The ability to recognize glaucoma in its early stages is critical in preventing long-term vision loss. This paper presents a two-dimensional empirical Littlewood - Paley (LP) wavelet transform (2D-EWT)-based method for glaucoma detection using retinal fundus pictures. For the decay of the preanalyzed photographs into different sub-bands, EWT is used in this investigation. High-frequency sub-band images are then used to compute the features. The ReliefF method chose the valuable descriptors from the extricated include set. Finally, selected descriptors are classified using the random forest (RF) classifier. We use the RIM-ONE public online glaucoma database for performance evaluation of the proposed framework.

AB - Glaucoma is a severe condition that causes eyesight loss. The ability to recognize glaucoma in its early stages is critical in preventing long-term vision loss. This paper presents a two-dimensional empirical Littlewood - Paley (LP) wavelet transform (2D-EWT)-based method for glaucoma detection using retinal fundus pictures. For the decay of the preanalyzed photographs into different sub-bands, EWT is used in this investigation. High-frequency sub-band images are then used to compute the features. The ReliefF method chose the valuable descriptors from the extricated include set. Finally, selected descriptors are classified using the random forest (RF) classifier. We use the RIM-ONE public online glaucoma database for performance evaluation of the proposed framework.

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DO - 10.1109/ICDT57929.2023.10151239

M3 - Conference contribution

AN - SCOPUS:85164594431

T3 - 2023 International Conference on Disruptive Technologies, ICDT 2023

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BT - 2023 International Conference on Disruptive Technologies, ICDT 2023

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Parashar D, Mishra O, Sharma K, Choudhary S. 2-D Empirical LP Wavelet Transform based Automated Framework for Glaucoma Screening. In 2023 International Conference on Disruptive Technologies, ICDT 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 695-697. (2023 International Conference on Disruptive Technologies, ICDT 2023). doi: 10.1109/ICDT57929.2023.10151239

2-D Empirical LP Wavelet Transform based Automated Framework for Glaucoma Screening

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