Applications of Artificial Intelligence in MR Image Acquisition and Reconstruction
Recently, artificial intelligence (AI) technology has shown potential clinical utility in a wide range of MRI fields. In particular, AI models for improving the efficiency of the image acquisition process and the quality of reconstructed images are being actively developed by the MR research commu...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
The Korean Society of Radiology
2022-11-01
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| Series: | 대한영상의학회지 |
| Online Access: | https://doi.org/10.3348/jksr.2022.0156 |
| _version_ | 1811321195886280704 |
|---|---|
| author | Junghwa Kang Yoonho Nam |
| author_facet | Junghwa Kang Yoonho Nam |
| author_sort | Junghwa Kang |
| collection | DOAJ |
| description | Recently, artificial intelligence (AI) technology has shown potential clinical utility in a wide range of MRI
fields. In particular, AI models for improving the efficiency of the image acquisition process and the
quality of reconstructed images are being actively developed by the MR research community. AI is expected
to further reduce acquisition times in various MRI protocols used in clinical practice when compared
to current parallel imaging techniques. Additionally, AI can help with tasks such as planning, parameter
optimization, artifact reduction, and quality assessment. Furthermore, AI is being actively
applied to automate MR image analysis such as image registration, segmentation, and object detection.
For this reason, it is important to consider the effects of protocols or devices in MR image analysis.
In this review article, we briefly introduced issues related to AI application of MR image acquisition and
reconstruction. |
| first_indexed | 2024-04-13T13:12:36Z |
| format | Article |
| id | doaj.art-21a9cd5ebd4b4b6a8ee18121d4ed0b07 |
| institution | Directory Open Access Journal |
| issn | 2288-2928 |
| language | English |
| last_indexed | 2024-04-13T13:12:36Z |
| publishDate | 2022-11-01 |
| publisher | The Korean Society of Radiology |
| record_format | Article |
| series | 대한영상의학회지 |
| spelling | doaj.art-21a9cd5ebd4b4b6a8ee18121d4ed0b072022-12-22T02:45:33ZengThe Korean Society of Radiology대한영상의학회지2288-29282022-11-0183612291239Applications of Artificial Intelligence in MR Image Acquisition and ReconstructionJunghwa KangYoonho NamRecently, artificial intelligence (AI) technology has shown potential clinical utility in a wide range of MRI fields. In particular, AI models for improving the efficiency of the image acquisition process and the quality of reconstructed images are being actively developed by the MR research community. AI is expected to further reduce acquisition times in various MRI protocols used in clinical practice when compared to current parallel imaging techniques. Additionally, AI can help with tasks such as planning, parameter optimization, artifact reduction, and quality assessment. Furthermore, AI is being actively applied to automate MR image analysis such as image registration, segmentation, and object detection. For this reason, it is important to consider the effects of protocols or devices in MR image analysis. In this review article, we briefly introduced issues related to AI application of MR image acquisition and reconstruction.https://doi.org/10.3348/jksr.2022.0156 |
| spellingShingle | Junghwa Kang Yoonho Nam Applications of Artificial Intelligence in MR Image Acquisition and Reconstruction 대한영상의학회지 |
| title | Applications of Artificial Intelligence in MR Image Acquisition and Reconstruction |
| title_full | Applications of Artificial Intelligence in MR Image Acquisition and Reconstruction |
| title_fullStr | Applications of Artificial Intelligence in MR Image Acquisition and Reconstruction |
| title_full_unstemmed | Applications of Artificial Intelligence in MR Image Acquisition and Reconstruction |
| title_short | Applications of Artificial Intelligence in MR Image Acquisition and Reconstruction |
| title_sort | applications of artificial intelligence in mr image acquisition and reconstruction |
| url | https://doi.org/10.3348/jksr.2022.0156 |
| work_keys_str_mv | AT junghwakang applicationsofartificialintelligenceinmrimageacquisitionandreconstruction AT yoonhonam applicationsofartificialintelligenceinmrimageacquisitionandreconstruction |