Role of artificial intelligence in medical image analysis

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.

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Publication Details

Journal
Chinese Medical Journal
Published
2025-10-24
DOI
https://doi.org/10.1097/cm9.0000000000003824
Citations
4
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
5.44
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article

Role of artificial intelligence in medical image analysis

Shouliang Qi, Huihan Wang, Qianqian He, Nan Xu et al.
4 citations
Chinese Medical Journal
Radiomics and Machine Learning in Medical Imaging
5.44
article

Role of artificial intelligence in medical image analysis

Shouliang Qi, Huihan Wang, Qianqian He, Nan Xu, Jiangdian Song, Zhihui Chang, Yu Shi, Lu Wang, Shimin Zhang, Xiujuan Qu, Yanan Wu, Xin Zhou, Lína Zhang, Yuming Zhu
article en
4 citations

Abstract

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.

Chinese Medical JournalVol. 138(22)
Fourth Affiliated Hospital of China Medical University (CN), First Hospital of China Medical University (CN), China Medical University (CN), Northeastern University (CN)
Openalex Percentile: Top 4%
Radiomics and Machine Learning in Medical Imaging
5.44
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