Applications of Deep Learning to MRI Images: A Survey
Deep learning provides exciting solutions in many fields, such as image analysis, natural language processing, and expert system, and is seen as a key method for various future applications. On account of its non-invasive and good soft tissue contrast, in recent years, Magnetic Resonance Imaging (MR...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Tsinghua University Press
2018-03-01
|
| Series: | Big Data Mining and Analytics |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2018.9020001 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832572794154516480 |
|---|---|
| author | Jin Liu Yi Pan Min Li Ziyue Chen Lu Tang Chengqian Lu Jianxin Wang |
| author_facet | Jin Liu Yi Pan Min Li Ziyue Chen Lu Tang Chengqian Lu Jianxin Wang |
| author_sort | Jin Liu |
| collection | DOAJ |
| description | Deep learning provides exciting solutions in many fields, such as image analysis, natural language processing, and expert system, and is seen as a key method for various future applications. On account of its non-invasive and good soft tissue contrast, in recent years, Magnetic Resonance Imaging (MRI) has been attracting increasing attention. With the development of deep learning, many innovative deep learning methods have been proposed to improve MRI image processing and analysis performance. The purpose of this article is to provide a comprehensive overview of deep learning-based MRI image processing and analysis. First, a brief introduction of deep learning and imaging modalities of MRI images is given. Then, common deep learning architectures are introduced. Next, deep learning applications of MRI images, such as image detection, image registration, image segmentation, and image classification are discussed. Subsequently, the advantages and weaknesses of several common tools are discussed, and several deep learning tools in the applications of MRI images are presented. Finally, an objective assessment of deep learning in MRI applications is presented, and future developments and trends with regard to deep learning for MRI images are addressed. |
| format | Article |
| id | doaj-art-25e87b29f4064d8ab13077b3a60369fc |
| institution | Kabale University |
| issn | 2096-0654 |
| language | English |
| publishDate | 2018-03-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj-art-25e87b29f4064d8ab13077b3a60369fc2025-02-02T06:49:44ZengTsinghua University PressBig Data Mining and Analytics2096-06542018-03-011111810.26599/BDMA.2018.9020001Applications of Deep Learning to MRI Images: A SurveyJin Liu0Yi Pan1Min Li2Ziyue Chen3Lu Tang4Chengqian Lu5Jianxin Wang6<institution content-type="dept">School of Information Science and Engineering</institution>, <institution>Central South University</institution>, <city>Changsha</city> <postal-code>410083</postal-code>, <country>China</country>.<institution content-type="dept">Department of Computer Science</institution>, <institution>Georgia State University</institution>, <city>Atlanta</city>, <state>GA</state><postal-code>30302</postal-code>, <country>USA</country>.<institution content-type="dept">School of Information Science and Engineering</institution>, <institution>Central South University</institution>, <city>Changsha</city> <postal-code>410083</postal-code>, <country>China</country>.<institution content-type="dept">Department of Computer Science</institution>, <institution>Georgia State University</institution>, <city>Atlanta</city>, <state>GA</state><postal-code>30302</postal-code>, <country>USA</country>.<institution content-type="dept">School of Information Science and Engineering</institution>, <institution>Central South University</institution>, <city>Changsha</city> <postal-code>410083</postal-code>, <country>China</country>.<institution content-type="dept">School of Information Science and Engineering</institution>, <institution>Central South University</institution>, <city>Changsha</city> <postal-code>410083</postal-code>, <country>China</country>.<institution content-type="dept">School of Information Science and Engineering</institution>, <institution>Central South University</institution>, <city>Changsha</city> <postal-code>410083</postal-code>, <country>China</country>.Deep learning provides exciting solutions in many fields, such as image analysis, natural language processing, and expert system, and is seen as a key method for various future applications. On account of its non-invasive and good soft tissue contrast, in recent years, Magnetic Resonance Imaging (MRI) has been attracting increasing attention. With the development of deep learning, many innovative deep learning methods have been proposed to improve MRI image processing and analysis performance. The purpose of this article is to provide a comprehensive overview of deep learning-based MRI image processing and analysis. First, a brief introduction of deep learning and imaging modalities of MRI images is given. Then, common deep learning architectures are introduced. Next, deep learning applications of MRI images, such as image detection, image registration, image segmentation, and image classification are discussed. Subsequently, the advantages and weaknesses of several common tools are discussed, and several deep learning tools in the applications of MRI images are presented. Finally, an objective assessment of deep learning in MRI applications is presented, and future developments and trends with regard to deep learning for MRI images are addressed.https://www.sciopen.com/article/10.26599/BDMA.2018.9020001magnetic resonance imagingdeep learningimage detectionimage registrationimage segmentationimage classification |
| spellingShingle | Jin Liu Yi Pan Min Li Ziyue Chen Lu Tang Chengqian Lu Jianxin Wang Applications of Deep Learning to MRI Images: A Survey Big Data Mining and Analytics magnetic resonance imaging deep learning image detection image registration image segmentation image classification |
| title | Applications of Deep Learning to MRI Images: A Survey |
| title_full | Applications of Deep Learning to MRI Images: A Survey |
| title_fullStr | Applications of Deep Learning to MRI Images: A Survey |
| title_full_unstemmed | Applications of Deep Learning to MRI Images: A Survey |
| title_short | Applications of Deep Learning to MRI Images: A Survey |
| title_sort | applications of deep learning to mri images a survey |
| topic | magnetic resonance imaging deep learning image detection image registration image segmentation image classification |
| url | https://www.sciopen.com/article/10.26599/BDMA.2018.9020001 |
| work_keys_str_mv | AT jinliu applicationsofdeeplearningtomriimagesasurvey AT yipan applicationsofdeeplearningtomriimagesasurvey AT minli applicationsofdeeplearningtomriimagesasurvey AT ziyuechen applicationsofdeeplearningtomriimagesasurvey AT lutang applicationsofdeeplearningtomriimagesasurvey AT chengqianlu applicationsofdeeplearningtomriimagesasurvey AT jianxinwang applicationsofdeeplearningtomriimagesasurvey |