Methodology for the Creation of a Medical Database: Case of Fundus imaging

Wilver Auccahuasi; Oscar Linares; Kitty Urbano; Karin Rojas; Gabriel Aiquipa; Tamara Pando-Ezcurra

doi:10.1109/ICAAIC56838.2023.10141187

Methodology for the Creation of a Medical Database: Case of Fundus imaging

Wilver Auccahuasi
, Oscar Linares
, Kitty Urbano
, Karin Rojas
, Gabriel Aiquipa
, Tamara Pando-Ezcurra

UPN Directorate of Research, Innovation, and Sustainability

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

Abstract

Currently, recognition systems based on the use of Artificial Intelligence techniques, are being used more frequently. For these systems to be trained, it is necessary to have a series of training images, known as dataset of images. This research study demonstrates a novel method to create a dataset of different types of images, with a demonstration applied to fundus images, in order to recognize exudates that are the first symptoms of diabetic retinopathy. The proposed method considers original fundus images, which identify characteristics of some pathology, and in this case, diabetic retinopathy. With these images, groups of images are generated to be able to build a dataset of images and that these can be used in the design of classification algorithms. As a result, this study presents a new dataset corresponding to image areas with presence of hard exudates. The proposed method can be scaled to different types and modalities of images.

Original language	English
Title of host publication	Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023
Pages	1685-1687
Number of pages	3
ISBN (Electronic)	9781665456302
DOIs	https://doi.org/10.1109/ICAAIC56838.2023.10141187
State	Published - 2023
Event	2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023 - Salem, India Duration: 4 May 2023 → 6 May 2023

Publication series

Name	Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023

Conference

Conference	2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023
Country/Territory	India
City	Salem
Period	4/05/23 → 6/05/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Diabetic retinopathy
Fundus imaging

Access to Document

10.1109/ICAAIC56838.2023.10141187

Cite this

Auccahuasi, W., Linares, O., Urbano, K., Rojas, K., Aiquipa, G., & Pando-Ezcurra, T. (2023). Methodology for the Creation of a Medical Database: Case of Fundus imaging. In Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023 (pp. 1685-1687). (Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023). https://doi.org/10.1109/ICAAIC56838.2023.10141187

Auccahuasi, Wilver ; Linares, Oscar ; Urbano, Kitty et al. / Methodology for the Creation of a Medical Database : Case of Fundus imaging. Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023. 2023. pp. 1685-1687 (Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023).

@inproceedings{71290d28d3d04d459341fa341ea012e0,

title = "Methodology for the Creation of a Medical Database: Case of Fundus imaging",

abstract = "Currently, recognition systems based on the use of Artificial Intelligence techniques, are being used more frequently. For these systems to be trained, it is necessary to have a series of training images, known as dataset of images. This research study demonstrates a novel method to create a dataset of different types of images, with a demonstration applied to fundus images, in order to recognize exudates that are the first symptoms of diabetic retinopathy. The proposed method considers original fundus images, which identify characteristics of some pathology, and in this case, diabetic retinopathy. With these images, groups of images are generated to be able to build a dataset of images and that these can be used in the design of classification algorithms. As a result, this study presents a new dataset corresponding to image areas with presence of hard exudates. The proposed method can be scaled to different types and modalities of images.",

keywords = "Diabetic retinopathy, Fundus imaging",

author = "Wilver Auccahuasi and Oscar Linares and Kitty Urbano and Karin Rojas and Gabriel Aiquipa and Tamara Pando-Ezcurra",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023 ; Conference date: 04-05-2023 Through 06-05-2023",

year = "2023",

doi = "10.1109/ICAAIC56838.2023.10141187",

language = "English",

series = "Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023",

pages = "1685--1687",

booktitle = "Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023",

}

Auccahuasi, W, Linares, O, Urbano, K, Rojas, K, Aiquipa, G & Pando-Ezcurra, T 2023, Methodology for the Creation of a Medical Database: Case of Fundus imaging. in Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023. Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023, pp. 1685-1687, 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023, Salem, India, 4/05/23. https://doi.org/10.1109/ICAAIC56838.2023.10141187

Methodology for the Creation of a Medical Database: Case of Fundus imaging. / Auccahuasi, Wilver; Linares, Oscar; Urbano, Kitty et al.
Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023. 2023. p. 1685-1687 (Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023).

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

TY - GEN

T1 - Methodology for the Creation of a Medical Database

T2 - 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023

AU - Auccahuasi, Wilver

AU - Linares, Oscar

AU - Urbano, Kitty

AU - Rojas, Karin

AU - Aiquipa, Gabriel

AU - Pando-Ezcurra, Tamara

PY - 2023

Y1 - 2023

N2 - Currently, recognition systems based on the use of Artificial Intelligence techniques, are being used more frequently. For these systems to be trained, it is necessary to have a series of training images, known as dataset of images. This research study demonstrates a novel method to create a dataset of different types of images, with a demonstration applied to fundus images, in order to recognize exudates that are the first symptoms of diabetic retinopathy. The proposed method considers original fundus images, which identify characteristics of some pathology, and in this case, diabetic retinopathy. With these images, groups of images are generated to be able to build a dataset of images and that these can be used in the design of classification algorithms. As a result, this study presents a new dataset corresponding to image areas with presence of hard exudates. The proposed method can be scaled to different types and modalities of images.

AB - Currently, recognition systems based on the use of Artificial Intelligence techniques, are being used more frequently. For these systems to be trained, it is necessary to have a series of training images, known as dataset of images. This research study demonstrates a novel method to create a dataset of different types of images, with a demonstration applied to fundus images, in order to recognize exudates that are the first symptoms of diabetic retinopathy. The proposed method considers original fundus images, which identify characteristics of some pathology, and in this case, diabetic retinopathy. With these images, groups of images are generated to be able to build a dataset of images and that these can be used in the design of classification algorithms. As a result, this study presents a new dataset corresponding to image areas with presence of hard exudates. The proposed method can be scaled to different types and modalities of images.

KW - Diabetic retinopathy

KW - Fundus imaging

UR - https://www.scopus.com/pages/publications/85163589686

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DO - 10.1109/ICAAIC56838.2023.10141187

M3 - Conference contribution

AN - SCOPUS:85163589686

T3 - Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023

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BT - Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023

Y2 - 4 May 2023 through 6 May 2023

ER -

Auccahuasi W, Linares O, Urbano K, Rojas K, Aiquipa G, Pando-Ezcurra T. Methodology for the Creation of a Medical Database: Case of Fundus imaging. In Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023. 2023. p. 1685-1687. (Proceedings of the 2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023). doi: 10.1109/ICAAIC56838.2023.10141187

Methodology for the Creation of a Medical Database: Case of Fundus imaging

Abstract

Publication series

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UN SDGs

Keywords

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