A survey of MRI-based brain tissue segmentation using deep learning
Abstract Segmentation of brain tissue from MR images provides detailed quantitative brain analysis for accurate diagnosis, detection, and classification of brain diseases, and plays an important role in neuroimaging research and clinical environments. Recently, a plethora of deep learning-based appr...
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| Format: | Article |
| Language: | English |
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Springer
2024-12-01
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| Series: | Complex & Intelligent Systems |
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| Online Access: | https://doi.org/10.1007/s40747-024-01639-1 |
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| _version_ | 1832571179387322368 |
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| author | Liang Wu Shirui Wang Jun Liu Lixia Hou Na Li Fei Su Xi Yang Weizhao Lu Jianfeng Qiu Ming Zhang Li Song |
| author_facet | Liang Wu Shirui Wang Jun Liu Lixia Hou Na Li Fei Su Xi Yang Weizhao Lu Jianfeng Qiu Ming Zhang Li Song |
| author_sort | Liang Wu |
| collection | DOAJ |
| description | Abstract Segmentation of brain tissue from MR images provides detailed quantitative brain analysis for accurate diagnosis, detection, and classification of brain diseases, and plays an important role in neuroimaging research and clinical environments. Recently, a plethora of deep learning-based approaches have been employed to achieve brain tissue segmentation in fetuses, infants, and adults with impressive outcomes. However, owing to the existence of noise, motion artifacts, and edge blurriness in MR images, automatically segmenting brain tissue accurately from MR images is still a very challenging task. This survey examines both deep learning and MRI, providing an overview of the latest advances in fetal, infant, and adult brain tissue segmentation techniques based on deep learning. It includes the performance and quantitative analysis of the state-of-the-art methods. Over 100 scientific papers covering various technical aspects, including network architecture, prior knowledge, and attention mechanisms, were reviewed and analyzed. This article also comprehensively discusses these technologies and their potential applications in the future. Brain tissue segmentation provides detailed quantitative brain analysis for accurate diagnosis, detection, and classification of brain diseases, and plays an important role in neuroimaging research and clinical environments. |
| format | Article |
| id | doaj-art-8606b35a9bb6449e885b2387908e3a0b |
| institution | Kabale University |
| issn | 2199-4536 2198-6053 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Springer |
| record_format | Article |
| series | Complex & Intelligent Systems |
| spelling | doaj-art-8606b35a9bb6449e885b2387908e3a0b2025-02-02T12:50:00ZengSpringerComplex & Intelligent Systems2199-45362198-60532024-12-0111111610.1007/s40747-024-01639-1A survey of MRI-based brain tissue segmentation using deep learningLiang Wu0Shirui Wang1Jun Liu2Lixia Hou3Na Li4Fei Su5Xi Yang6Weizhao Lu7Jianfeng Qiu8Ming Zhang9Li Song10School of Radiology, Shandong First Medical University and Shandong Academy of Medical SciencesSchool of Radiology, Shandong First Medical University and Shandong Academy of Medical SciencesDepartment of Radiology, Taian Maternal and Child Health HospitalSchool of Radiology, Shandong First Medical University and Shandong Academy of Medical SciencesSchool of Radiology, Shandong First Medical University and Shandong Academy of Medical SciencesSchool of Radiology, Shandong First Medical University and Shandong Academy of Medical SciencesDepartment of Mathematics and Statistics, Graduate School of Arts, Sciences Boston UniversitySchool of Radiology, Shandong First Medical University and Shandong Academy of Medical SciencesSchool of Radiology, Shandong First Medical University and Shandong Academy of Medical SciencesSchool of Information Engineering, Inner Mongolia University of Science and TechnologySchool of Radiology, Shandong First Medical University and Shandong Academy of Medical SciencesAbstract Segmentation of brain tissue from MR images provides detailed quantitative brain analysis for accurate diagnosis, detection, and classification of brain diseases, and plays an important role in neuroimaging research and clinical environments. Recently, a plethora of deep learning-based approaches have been employed to achieve brain tissue segmentation in fetuses, infants, and adults with impressive outcomes. However, owing to the existence of noise, motion artifacts, and edge blurriness in MR images, automatically segmenting brain tissue accurately from MR images is still a very challenging task. This survey examines both deep learning and MRI, providing an overview of the latest advances in fetal, infant, and adult brain tissue segmentation techniques based on deep learning. It includes the performance and quantitative analysis of the state-of-the-art methods. Over 100 scientific papers covering various technical aspects, including network architecture, prior knowledge, and attention mechanisms, were reviewed and analyzed. This article also comprehensively discusses these technologies and their potential applications in the future. Brain tissue segmentation provides detailed quantitative brain analysis for accurate diagnosis, detection, and classification of brain diseases, and plays an important role in neuroimaging research and clinical environments.https://doi.org/10.1007/s40747-024-01639-1Brain tissue segmentationSurveyFetalInfantAdultDeep learning |
| spellingShingle | Liang Wu Shirui Wang Jun Liu Lixia Hou Na Li Fei Su Xi Yang Weizhao Lu Jianfeng Qiu Ming Zhang Li Song A survey of MRI-based brain tissue segmentation using deep learning Complex & Intelligent Systems Brain tissue segmentation Survey Fetal Infant Adult Deep learning |
| title | A survey of MRI-based brain tissue segmentation using deep learning |
| title_full | A survey of MRI-based brain tissue segmentation using deep learning |
| title_fullStr | A survey of MRI-based brain tissue segmentation using deep learning |
| title_full_unstemmed | A survey of MRI-based brain tissue segmentation using deep learning |
| title_short | A survey of MRI-based brain tissue segmentation using deep learning |
| title_sort | survey of mri based brain tissue segmentation using deep learning |
| topic | Brain tissue segmentation Survey Fetal Infant Adult Deep learning |
| url | https://doi.org/10.1007/s40747-024-01639-1 |
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