Development of Mobile Application for Detection and Grading of Diabetic Retinopathy

Kuryati Kipli; Lee Yee Hui; Nurul Mirza Afiqah Tajudin; Rohana Sapawi; Siti Kudnie Sahari; Dayang Azra Awang Mat; M. A. Jalil; Kanad Ray; M. Shamim Kaiser; Mufti Mahmud

doi:10.1007/978-981-16-8826-3_29

Development of Mobile Application for Detection and Grading of Diabetic Retinopathy

Kuryati Kipli^*
, Lee Yee Hui
, Nurul Mirza Afiqah Tajudin
, Rohana Sapawi
, Siti Kudnie Sahari
, Dayang Azra Awang Mat
, M. A. Jalil
, Kanad Ray
, M. Shamim Kaiser
, Mufti Mahmud

^*Corresponding author for this work

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

6 Scopus citations

Abstract

The key to preventing blindness caused by diabetic retinopathy (DR) is regular screening and early recognition during its early stages. Currently, DR grading is done manually by ophthalmologists and trained graders where the process is time-consuming. Therefore, this paper aims to develop a mobile app that can provide DR detection and grading without a professional or doctor. The patients will be referred to ophthalmologists if further evaluations are required. This research builds an image classification within a mobile application by using deep learning techniques which utilized the Google AI technologies: Google TensorFlow and Google Cloud Platform (Cloud AutoML and Cloud storage). Image classification is performed in two layers which involve DR detection and grading. A total of 12,062 fundus images are chosen from the dataset collected and undergo image preprocessing. The preprocessed images are used to train the model in TensorFlow and Cloud AutoML, respectively. The model will be implemented into the mobile application after being trained with high accuracy. The final test accuracy for the MobileNet pretrained model is 82.9%, while averaging precision for the model of Cloud AutoML is 75%. Further research is required to improve the stability of this algorithm and mobile app for real clinical environment settings.

Original language	English
Title of host publication	Proceedings of Trends in Electronics and Health Informatics, TEHI 2021
Editors	M. Shamim Kaiser, Anirban Bandyopadhyay, Kanad Ray, Raghvendra Singh, Vishal Nagar
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	339-349
Number of pages	11
ISBN (Print)	9789811688256
DOIs	https://doi.org/10.1007/978-981-16-8826-3_29
State	Published - 2022
Externally published	Yes
Event	1st International Conference on Trends in Electronics and Health Informatics, TEHI 2021 - Virtual, Online Duration: 16 Dec 2021 → 17 Dec 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	376
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	1st International Conference on Trends in Electronics and Health Informatics, TEHI 2021
City	Virtual, Online
Period	16/12/21 → 17/12/21

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Keywords

Cloud AutoML
Diabetic retinopathy
Google TensorFlow
Google cloud platform
Image classification
Mobile application

ASJC Scopus subject areas

Control and Systems Engineering
Signal Processing
Computer Networks and Communications

Access to Document

10.1007/978-981-16-8826-3_29

Cite this

Kipli, K., Hui, L. Y., Tajudin, N. M. A., Sapawi, R., Sahari, S. K., Mat, D. A. A., Jalil, M. A., Ray, K., Shamim Kaiser, M., & Mahmud, M. (2022). Development of Mobile Application for Detection and Grading of Diabetic Retinopathy. In M. S. Kaiser, A. Bandyopadhyay, K. Ray, R. Singh, & V. Nagar (Eds.), Proceedings of Trends in Electronics and Health Informatics, TEHI 2021 (pp. 339-349). (Lecture Notes in Networks and Systems; Vol. 376). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-8826-3_29

Kipli, Kuryati ; Hui, Lee Yee ; Tajudin, Nurul Mirza Afiqah et al. / Development of Mobile Application for Detection and Grading of Diabetic Retinopathy. Proceedings of Trends in Electronics and Health Informatics, TEHI 2021. editor / M. Shamim Kaiser ; Anirban Bandyopadhyay ; Kanad Ray ; Raghvendra Singh ; Vishal Nagar. Springer Science and Business Media Deutschland GmbH, 2022. pp. 339-349 (Lecture Notes in Networks and Systems).

@inproceedings{6cc1333383424f8582aec0718a737fac,

title = "Development of Mobile Application for Detection and Grading of Diabetic Retinopathy",

abstract = "The key to preventing blindness caused by diabetic retinopathy (DR) is regular screening and early recognition during its early stages. Currently, DR grading is done manually by ophthalmologists and trained graders where the process is time-consuming. Therefore, this paper aims to develop a mobile app that can provide DR detection and grading without a professional or doctor. The patients will be referred to ophthalmologists if further evaluations are required. This research builds an image classification within a mobile application by using deep learning techniques which utilized the Google AI technologies: Google TensorFlow and Google Cloud Platform (Cloud AutoML and Cloud storage). Image classification is performed in two layers which involve DR detection and grading. A total of 12,062 fundus images are chosen from the dataset collected and undergo image preprocessing. The preprocessed images are used to train the model in TensorFlow and Cloud AutoML, respectively. The model will be implemented into the mobile application after being trained with high accuracy. The final test accuracy for the MobileNet pretrained model is 82.9\%, while averaging precision for the model of Cloud AutoML is 75\%. Further research is required to improve the stability of this algorithm and mobile app for real clinical environment settings.",

keywords = "Cloud AutoML, Diabetic retinopathy, Google TensorFlow, Google cloud platform, Image classification, Mobile application",

author = "Kuryati Kipli and Hui, \{Lee Yee\} and Tajudin, \{Nurul Mirza Afiqah\} and Rohana Sapawi and Sahari, \{Siti Kudnie\} and Mat, \{Dayang Azra Awang\} and Jalil, \{M. A.\} and Kanad Ray and \{Shamim Kaiser\}, M. and Mufti Mahmud",

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Kipli, K, Hui, LY, Tajudin, NMA, Sapawi, R, Sahari, SK, Mat, DAA, Jalil, MA, Ray, K, Shamim Kaiser, M & Mahmud, M 2022, Development of Mobile Application for Detection and Grading of Diabetic Retinopathy. in MS Kaiser, A Bandyopadhyay, K Ray, R Singh & V Nagar (eds), Proceedings of Trends in Electronics and Health Informatics, TEHI 2021. Lecture Notes in Networks and Systems, vol. 376, Springer Science and Business Media Deutschland GmbH, pp. 339-349, 1st International Conference on Trends in Electronics and Health Informatics, TEHI 2021, Virtual, Online, 16/12/21. https://doi.org/10.1007/978-981-16-8826-3_29

Development of Mobile Application for Detection and Grading of Diabetic Retinopathy. / Kipli, Kuryati; Hui, Lee Yee; Tajudin, Nurul Mirza Afiqah et al.
Proceedings of Trends in Electronics and Health Informatics, TEHI 2021. ed. / M. Shamim Kaiser; Anirban Bandyopadhyay; Kanad Ray; Raghvendra Singh; Vishal Nagar. Springer Science and Business Media Deutschland GmbH, 2022. p. 339-349 (Lecture Notes in Networks and Systems; Vol. 376).

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

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AU - Hui, Lee Yee

AU - Tajudin, Nurul Mirza Afiqah

AU - Sapawi, Rohana

AU - Sahari, Siti Kudnie

AU - Mat, Dayang Azra Awang

AU - Jalil, M. A.

AU - Ray, Kanad

AU - Shamim Kaiser, M.

AU - Mahmud, Mufti

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Kipli K, Hui LY, Tajudin NMA, Sapawi R, Sahari SK, Mat DAA et al. Development of Mobile Application for Detection and Grading of Diabetic Retinopathy. In Kaiser MS, Bandyopadhyay A, Ray K, Singh R, Nagar V, editors, Proceedings of Trends in Electronics and Health Informatics, TEHI 2021. Springer Science and Business Media Deutschland GmbH. 2022. p. 339-349. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-16-8826-3_29

Development of Mobile Application for Detection and Grading of Diabetic Retinopathy

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this