Applications of Deep Learning in Medical Image Analysis: a Comprehensive Review of Recent Advances and Challenges

Yuqin Guo

doi:10.47297/wspbdsWSP2752-630541.20250503

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Applications of Deep Learning in Medical Image Analysis: a Comprehensive Review of Recent Advances and Challenges

Volume 5, Issue 3

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Applications of Deep Learning in Medical Image Analysis: a Comprehensive Review of Recent Advances and Challenges
Applications of Deep Learning in Medical Image Analysis: a Comprehensive Review of Recent Advances and Challenges
Department of Computer Science and Engineering and Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong, 999077, China
Vol. 5, Issue 3, Pages: 194-199(2025)
Published：30 September 2025
DOI：10.47297/wspbdsWSP2752-630541.20250503
Accepted：

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Guo Yuqin.Applications of Deep Learning in Medical Image Analysis: a Comprehensive Review of Recent Advances and Challenges[J].Biomedical Data Science,2025,05(03):194-199.
DOI：

Guo Yuqin.Applications of Deep Learning in Medical Image Analysis: a Comprehensive Review of Recent Advances and Challenges[J].Biomedical Data Science,2025,05(03):194-199. DOI： 10.47297/wspbdsWSP2752-630541.20250503.

摘要

Abstract

Medical imaging serves as a cornerstone in modern healthcare

enabling non-invasive diagnosis

treatment planning

and patient follow-up through modalities like X-rays

CT scans

MRI

ultrasound

and PET scans. This comprehensive review delves into the transformative impact of deep learning on the field

mentioning core methodologies like CNNs

RNNs

Autoencoders

GANs

ViTs

and hybrid models. Applications are dissected across clinical domains including oncology

neurology

cardiology

pulmonology

ophthalmology

dermatology

and orthopedics

alongside tasks ranging from classification and segmentation to detection

reg- istration

reconstruction

synthesis

and forecasting. Achievements are highlighted

particularly in achieving superior accuracy for classification and precise delineation in segmentation across varied medical contexts.

关键词

Keywords

references

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