Anomaly Detection in Red Reflex Images Using Deep Learning Approaches

Setnipat Kriangsakdachai; Srisupa Palakvangsa Na Ayudhya; Worapan Kusakunniran; Wongchanok Devakula Na Ayudhya; Chayapon Chantrasagul; Rungsimun Manasboonpermpool; Kanchalika Sathianvichitr; Prapasson Sangsre; Thammanoon Surachatkumtonekul

doi:10.1109/TENCON55691.2022.9977626

Anomaly Detection in Red Reflex Images Using Deep Learning Approaches

Setnipat Kriangsakdachai
, Srisupa Palakvangsa Na Ayudhya
, Worapan Kusakunniran
, Wongchanok Devakula Na Ayudhya
, Chayapon Chantrasagul
, Rungsimun Manasboonpermpool
, Kanchalika Sathianvichitr
, Prapasson Sangsre
, Thammanoon Surachatkumtonekul

Mahidol University
Siriraj Hospital

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

3 Citations (Scopus)

Abstract

Amblyopia is a noteworthy disease in children leading to visual loss. This work focuses on creating a deep learning model for the detection of Amblyopia factors in patients wearing masks under the COVID-19 pandemic.

Original language	English
Title of host publication	Proceedings of 2022 IEEE Region 10 International Conference, TENCON 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665450959
DOIs	https://doi.org/10.1109/TENCON55691.2022.9977626
Publication status	Published - 2022
Event	2022 IEEE Region 10 International Conference, TENCON 2022 - Virtual, Online, China Duration: 1 Nov 2022 → 4 Nov 2022

Publication series

Name	IEEE Region 10 Annual International Conference, Proceedings/TENCON
Volume	2022-November
ISSN (Print)	2159-3442
ISSN (Electronic)	2159-3450

Conference

Conference	2022 IEEE Region 10 International Conference, TENCON 2022
Country/Territory	China
City	Virtual, Online
Period	1/11/22 → 4/11/22

Keywords

Amblyopia
Convolutional neural network
Deep learning
MTCNN
Mask R-CNN
Red reflex

Access to Document

10.1109/TENCON55691.2022.9977626

Cite this

Kriangsakdachai, S., Ayudhya, S. P. N., Kusakunniran, W., Ayudhya, W. D. N., Chantrasagul, C., Manasboonpermpool, R., Sathianvichitr, K., Sangsre, P., & Surachatkumtonekul, T. (2022). Anomaly Detection in Red Reflex Images Using Deep Learning Approaches. In Proceedings of 2022 IEEE Region 10 International Conference, TENCON 2022 (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2022-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TENCON55691.2022.9977626

Kriangsakdachai, Setnipat ; Ayudhya, Srisupa Palakvangsa Na ; Kusakunniran, Worapan et al. / Anomaly Detection in Red Reflex Images Using Deep Learning Approaches. Proceedings of 2022 IEEE Region 10 International Conference, TENCON 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (IEEE Region 10 Annual International Conference, Proceedings/TENCON).

@inproceedings{48c937417abd4d89884dc84c24bd65b5,

title = "Anomaly Detection in Red Reflex Images Using Deep Learning Approaches",

abstract = "Amblyopia is a noteworthy disease in children leading to visual loss. This work focuses on creating a deep learning model for the detection of Amblyopia factors in patients wearing masks under the COVID-19 pandemic.",

keywords = "Amblyopia, Convolutional neural network, Deep learning, MTCNN, Mask R-CNN, Red reflex",

author = "Setnipat Kriangsakdachai and Ayudhya, \{Srisupa Palakvangsa Na\} and Worapan Kusakunniran and Ayudhya, \{Wongchanok Devakula Na\} and Chayapon Chantrasagul and Rungsimun Manasboonpermpool and Kanchalika Sathianvichitr and Prapasson Sangsre and Thammanoon Surachatkumtonekul",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE Region 10 International Conference, TENCON 2022 ; Conference date: 01-11-2022 Through 04-11-2022",

year = "2022",

doi = "10.1109/TENCON55691.2022.9977626",

language = "English",

series = "IEEE Region 10 Annual International Conference, Proceedings/TENCON",

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

booktitle = "Proceedings of 2022 IEEE Region 10 International Conference, TENCON 2022",

}

Kriangsakdachai, S, Ayudhya, SPN , Kusakunniran, W, Ayudhya, WDN, Chantrasagul, C, Manasboonpermpool, R, Sathianvichitr, K, Sangsre, P & Surachatkumtonekul, T 2022, Anomaly Detection in Red Reflex Images Using Deep Learning Approaches. in Proceedings of 2022 IEEE Region 10 International Conference, TENCON 2022. IEEE Region 10 Annual International Conference, Proceedings/TENCON, vol. 2022-November, Institute of Electrical and Electronics Engineers Inc., 2022 IEEE Region 10 International Conference, TENCON 2022, Virtual, Online, China, 1/11/22. https://doi.org/10.1109/TENCON55691.2022.9977626

Anomaly Detection in Red Reflex Images Using Deep Learning Approaches. / Kriangsakdachai, Setnipat; Ayudhya, Srisupa Palakvangsa Na ; Kusakunniran, Worapan et al.
Proceedings of 2022 IEEE Region 10 International Conference, TENCON 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2022-November).

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

TY - GEN

T1 - Anomaly Detection in Red Reflex Images Using Deep Learning Approaches

AU - Kriangsakdachai, Setnipat

AU - Ayudhya, Srisupa Palakvangsa Na

AU - Kusakunniran, Worapan

AU - Ayudhya, Wongchanok Devakula Na

AU - Chantrasagul, Chayapon

AU - Manasboonpermpool, Rungsimun

AU - Sathianvichitr, Kanchalika

AU - Sangsre, Prapasson

AU - Surachatkumtonekul, Thammanoon

PY - 2022

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N2 - Amblyopia is a noteworthy disease in children leading to visual loss. This work focuses on creating a deep learning model for the detection of Amblyopia factors in patients wearing masks under the COVID-19 pandemic.

AB - Amblyopia is a noteworthy disease in children leading to visual loss. This work focuses on creating a deep learning model for the detection of Amblyopia factors in patients wearing masks under the COVID-19 pandemic.

KW - Amblyopia

KW - Convolutional neural network

KW - Deep learning

KW - MTCNN

KW - Mask R-CNN

KW - Red reflex

UR - https://www.scopus.com/pages/publications/85145649664

U2 - 10.1109/TENCON55691.2022.9977626

DO - 10.1109/TENCON55691.2022.9977626

M3 - Conference contribution

AN - SCOPUS:85145649664

T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON

BT - Proceedings of 2022 IEEE Region 10 International Conference, TENCON 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 IEEE Region 10 International Conference, TENCON 2022

Y2 - 1 November 2022 through 4 November 2022

ER -

Kriangsakdachai S, Ayudhya SPN , Kusakunniran W, Ayudhya WDN, Chantrasagul C, Manasboonpermpool R et al. Anomaly Detection in Red Reflex Images Using Deep Learning Approaches. In Proceedings of 2022 IEEE Region 10 International Conference, TENCON 2022. Institute of Electrical and Electronics Engineers Inc. 2022. (IEEE Region 10 Annual International Conference, Proceedings/TENCON). doi: 10.1109/TENCON55691.2022.9977626

Anomaly Detection in Red Reflex Images Using Deep Learning Approaches

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Keywords

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