A Concept-Based Review on Generative Adversarial Network for Generating Super Resolution Medical Image Using SWOT Analysis

Saba Ibrahim David; Sulaimon A. Bashir; Mohammed D. Abdulmalik

doi:10.1109/ITED56637.2022.10051633

A Concept-Based Review on Generative Adversarial Network for Generating Super Resolution Medical Image Using SWOT Analysis

Saba Ibrahim David
, Sulaimon A. Bashir
, Mohammed D. Abdulmalik

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

1 Scopus citations

Abstract

Several alarming health challenges are urging medical experts and practitioners to research and develop new approaches to diagnose, detect and control the early spread of deadly diseases. One of the most challenging is Coronavirus Infection (Covid-19). Models have been proposed to detect and diagnose early infection of the virus to attain proper precautions against the Covid-19 virus. However, some researchers adopt parameter optimization to attain better accuracy on the Chest X-ray images of covid-19 and other related diseases. Hence, this research work adopts a hybridized cascaded feature extraction technique (Local Binary Pattern LBP and Histogram of Oriented Gradients HOG) and Convolutional Neural Network CNN for the deep learning classification model. The merging of LBP and HOG feature extraction significantly improved the performance level of the deep-learning CNN classifier. As a result, 95% accuracy, 92% precision, and 93% recall are attained by the proposed model.

Original language	English
Title of host publication	Proceedings of the 5th International Conference on Information Technology for Education and Development
Subtitle of host publication	Changing the Narratives Through Building a Secure Society with Disruptive Technologies, ITED 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509064229
DOIs	https://doi.org/10.1109/ITED56637.2022.10051633
State	Published - 2022
Externally published	Yes
Event	5th International Conference on Information Technology for Education and Development, ITED 2022 - Abuja, Nigeria Duration: 1 Nov 2022 → 3 Nov 2022

Publication series

Name	Proceedings of the 5th International Conference on Information Technology for Education and Development: Changing the Narratives Through Building a Secure Society with Disruptive Technologies, ITED 2022

Conference

Conference	5th International Conference on Information Technology for Education and Development, ITED 2022
Country/Territory	Nigeria
City	Abuja
Period	1/11/22 → 3/11/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

GAN
concept based
medical image
super-resolution
swot analysis

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications
Information Systems
Safety, Risk, Reliability and Quality
Development
Education

Access to Document

10.1109/ITED56637.2022.10051633

Cite this

David, S. I., Bashir, S. A., & Abdulmalik, M. D. (2022). A Concept-Based Review on Generative Adversarial Network for Generating Super Resolution Medical Image Using SWOT Analysis. In Proceedings of the 5th International Conference on Information Technology for Education and Development: Changing the Narratives Through Building a Secure Society with Disruptive Technologies, ITED 2022 (Proceedings of the 5th International Conference on Information Technology for Education and Development: Changing the Narratives Through Building a Secure Society with Disruptive Technologies, ITED 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITED56637.2022.10051633

David, Saba Ibrahim ; Bashir, Sulaimon A. ; Abdulmalik, Mohammed D. / A Concept-Based Review on Generative Adversarial Network for Generating Super Resolution Medical Image Using SWOT Analysis. Proceedings of the 5th International Conference on Information Technology for Education and Development: Changing the Narratives Through Building a Secure Society with Disruptive Technologies, ITED 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (Proceedings of the 5th International Conference on Information Technology for Education and Development: Changing the Narratives Through Building a Secure Society with Disruptive Technologies, ITED 2022).

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title = "A Concept-Based Review on Generative Adversarial Network for Generating Super Resolution Medical Image Using SWOT Analysis",

abstract = "Several alarming health challenges are urging medical experts and practitioners to research and develop new approaches to diagnose, detect and control the early spread of deadly diseases. One of the most challenging is Coronavirus Infection (Covid-19). Models have been proposed to detect and diagnose early infection of the virus to attain proper precautions against the Covid-19 virus. However, some researchers adopt parameter optimization to attain better accuracy on the Chest X-ray images of covid-19 and other related diseases. Hence, this research work adopts a hybridized cascaded feature extraction technique (Local Binary Pattern LBP and Histogram of Oriented Gradients HOG) and Convolutional Neural Network CNN for the deep learning classification model. The merging of LBP and HOG feature extraction significantly improved the performance level of the deep-learning CNN classifier. As a result, 95\% accuracy, 92\% precision, and 93\% recall are attained by the proposed model.",

keywords = "GAN, concept based, medical image, super-resolution, swot analysis",

author = "David, \{Saba Ibrahim\} and Bashir, \{Sulaimon A.\} and Abdulmalik, \{Mohammed D.\}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 5th International Conference on Information Technology for Education and Development, ITED 2022 ; Conference date: 01-11-2022 Through 03-11-2022",

year = "2022",

doi = "10.1109/ITED56637.2022.10051633",

language = "English",

series = "Proceedings of the 5th International Conference on Information Technology for Education and Development: Changing the Narratives Through Building a Secure Society with Disruptive Technologies, ITED 2022",

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David, SI, Bashir, SA & Abdulmalik, MD 2022, A Concept-Based Review on Generative Adversarial Network for Generating Super Resolution Medical Image Using SWOT Analysis. in Proceedings of the 5th International Conference on Information Technology for Education and Development: Changing the Narratives Through Building a Secure Society with Disruptive Technologies, ITED 2022. Proceedings of the 5th International Conference on Information Technology for Education and Development: Changing the Narratives Through Building a Secure Society with Disruptive Technologies, ITED 2022, Institute of Electrical and Electronics Engineers Inc., 5th International Conference on Information Technology for Education and Development, ITED 2022, Abuja, Nigeria, 1/11/22. https://doi.org/10.1109/ITED56637.2022.10051633

A Concept-Based Review on Generative Adversarial Network for Generating Super Resolution Medical Image Using SWOT Analysis. / David, Saba Ibrahim; Bashir, Sulaimon A.; Abdulmalik, Mohammed D.
Proceedings of the 5th International Conference on Information Technology for Education and Development: Changing the Narratives Through Building a Secure Society with Disruptive Technologies, ITED 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (Proceedings of the 5th International Conference on Information Technology for Education and Development: Changing the Narratives Through Building a Secure Society with Disruptive Technologies, ITED 2022).

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

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PY - 2022

Y1 - 2022

N2 - Several alarming health challenges are urging medical experts and practitioners to research and develop new approaches to diagnose, detect and control the early spread of deadly diseases. One of the most challenging is Coronavirus Infection (Covid-19). Models have been proposed to detect and diagnose early infection of the virus to attain proper precautions against the Covid-19 virus. However, some researchers adopt parameter optimization to attain better accuracy on the Chest X-ray images of covid-19 and other related diseases. Hence, this research work adopts a hybridized cascaded feature extraction technique (Local Binary Pattern LBP and Histogram of Oriented Gradients HOG) and Convolutional Neural Network CNN for the deep learning classification model. The merging of LBP and HOG feature extraction significantly improved the performance level of the deep-learning CNN classifier. As a result, 95% accuracy, 92% precision, and 93% recall are attained by the proposed model.

AB - Several alarming health challenges are urging medical experts and practitioners to research and develop new approaches to diagnose, detect and control the early spread of deadly diseases. One of the most challenging is Coronavirus Infection (Covid-19). Models have been proposed to detect and diagnose early infection of the virus to attain proper precautions against the Covid-19 virus. However, some researchers adopt parameter optimization to attain better accuracy on the Chest X-ray images of covid-19 and other related diseases. Hence, this research work adopts a hybridized cascaded feature extraction technique (Local Binary Pattern LBP and Histogram of Oriented Gradients HOG) and Convolutional Neural Network CNN for the deep learning classification model. The merging of LBP and HOG feature extraction significantly improved the performance level of the deep-learning CNN classifier. As a result, 95% accuracy, 92% precision, and 93% recall are attained by the proposed model.

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David SI, Bashir SA, Abdulmalik MD. A Concept-Based Review on Generative Adversarial Network for Generating Super Resolution Medical Image Using SWOT Analysis. In Proceedings of the 5th International Conference on Information Technology for Education and Development: Changing the Narratives Through Building a Secure Society with Disruptive Technologies, ITED 2022. Institute of Electrical and Electronics Engineers Inc. 2022. (Proceedings of the 5th International Conference on Information Technology for Education and Development: Changing the Narratives Through Building a Secure Society with Disruptive Technologies, ITED 2022). doi: 10.1109/ITED56637.2022.10051633

A Concept-Based Review on Generative Adversarial Network for Generating Super Resolution Medical Image Using SWOT Analysis

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this