A bibliometric and visual analysis of artificial intelligence technologies-enhanced brain MRI research

文献类型： 外文期刊

第一作者： Chen, Xieling

作者： Chen, Xieling;Zhang, Xinxin;Xie, Haoran;Tao, Xiaohui;Wang, Fu Lee;Xie, Nengfu;Hao, Tianyong

作者机构：

关键词： Magnetic resonance imaging; Artificial intelligence; Latent Dirichlet allocation; Research topics

期刊名称：MULTIMEDIA TOOLS AND APPLICATIONS （ 影响因子：2.757； 五年影响因子：2.517 ）

ISSN： 1380-7501

年卷期：

页码：

收录情况： SCI

摘要： With the advances and development of imaging and computer technologies, the application of artificial intelligence (AI) in the processing of magnetic resonance imaging (MRI) data has become a significant research field. Based on 2572 research articles concerning AI-enhanced brain MRI processing, this study provides a latent Dirichlet allocation based bibliometric analysis for the exploration of the status, trends, major research issues, and potential future directions of the research field. The trend analyses of articles and citations demonstrate a flourishing and increasing impact of the research.Neuroimageis the most prolific and influential journal. The USA andUniversity College Londonhave contributed the most to the research. The collaboration between European countries is very close. Essential research issues such asImage segmentation,Mental disorder,Functional network connectivity, andAlzheimer's diseasehave been uncovered. Potential inter-topic research directions such asFunctional network connectivityandMental disorder,Image segmentationandImage classification,Cognitive impairmentandDiffusion imaging, as well asSense and memoryandEmotion and feedback, have been highlighted.

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