Review on Deep Learning based Medical Image Processing

Aman Agarwal; Rakesh Kumar; Meenu Gupta

doi:10.1109/CCET56606.2022.10080703

Review on Deep Learning based Medical Image Processing

Aman Agarwal
, Rakesh Kumar
, Meenu Gupta

Chandigarh University

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

31 Scopus citations

Abstract

Deep learning (DL) has made extensive progress in many exploration regions. Computer vision is one of the most trending fields advancing due to extensive research in developing DL models, mainly focusing on image pattern recognition. These days, numerous specialists attempt to track down answers for issues in different fields under the illumination of DL techniques. In this review, important information is added about DL models and testing points specialists can use in DL. This study explored DL and concentrates on what advancements are made in the most famous fields, for example, Medical Image segmentation, automated disease classification, 4D Motion Estimation, etc. Moreover, this study discusses the leftover difficulties of these examination regions that DL can tackle and talks about future subjects to help scientists, especially in handling Medical Images.

Original language	English
Title of host publication	Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665454155
DOIs	https://doi.org/10.1109/CCET56606.2022.10080703
State	Published - 2022
Externally published	Yes
Event	2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022 - Bhopal, India Duration: 23 Dec 2022 → 24 Dec 2022

Publication series

Name	Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022

Conference

Conference	2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022
Country/Territory	India
City	Bhopal
Period	23/12/22 → 24/12/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Convolutional Neural Network (CNN)
DL
U-Net
medical image segmentation
residual learning

Access to Document

10.1109/CCET56606.2022.10080703

Cite this

Agarwal, A., Kumar, R., & Gupta, M. (2022). Review on Deep Learning based Medical Image Processing. In Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022 (Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCET56606.2022.10080703

Agarwal, Aman ; Kumar, Rakesh ; Gupta, Meenu. / Review on Deep Learning based Medical Image Processing. Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022).

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title = "Review on Deep Learning based Medical Image Processing",

abstract = "Deep learning (DL) has made extensive progress in many exploration regions. Computer vision is one of the most trending fields advancing due to extensive research in developing DL models, mainly focusing on image pattern recognition. These days, numerous specialists attempt to track down answers for issues in different fields under the illumination of DL techniques. In this review, important information is added about DL models and testing points specialists can use in DL. This study explored DL and concentrates on what advancements are made in the most famous fields, for example, Medical Image segmentation, automated disease classification, 4D Motion Estimation, etc. Moreover, this study discusses the leftover difficulties of these examination regions that DL can tackle and talks about future subjects to help scientists, especially in handling Medical Images.",

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author = "Aman Agarwal and Rakesh Kumar and Meenu Gupta",

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doi = "10.1109/CCET56606.2022.10080703",

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series = "Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022",

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Agarwal, A, Kumar, R & Gupta, M 2022, Review on Deep Learning based Medical Image Processing. in Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022. Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022, Institute of Electrical and Electronics Engineers Inc., 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022, Bhopal, India, 23/12/22. https://doi.org/10.1109/CCET56606.2022.10080703

Review on Deep Learning based Medical Image Processing. / Agarwal, Aman; Kumar, Rakesh; Gupta, Meenu.
Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022).

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

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AB - Deep learning (DL) has made extensive progress in many exploration regions. Computer vision is one of the most trending fields advancing due to extensive research in developing DL models, mainly focusing on image pattern recognition. These days, numerous specialists attempt to track down answers for issues in different fields under the illumination of DL techniques. In this review, important information is added about DL models and testing points specialists can use in DL. This study explored DL and concentrates on what advancements are made in the most famous fields, for example, Medical Image segmentation, automated disease classification, 4D Motion Estimation, etc. Moreover, this study discusses the leftover difficulties of these examination regions that DL can tackle and talks about future subjects to help scientists, especially in handling Medical Images.

KW - Convolutional Neural Network (CNN)

KW - DL

KW - U-Net

KW - medical image segmentation

KW - residual learning

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Agarwal A, Kumar R, Gupta M. Review on Deep Learning based Medical Image Processing. In Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022. Institute of Electrical and Electronics Engineers Inc. 2022. (Proceedings of 2022 IEEE International Conference on Current Development in Engineering and Technology, CCET 2022). doi: 10.1109/CCET56606.2022.10080703

Review on Deep Learning based Medical Image Processing

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

Access to Document

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