Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance
This open access LNCS volume 15515 constitutes the refereed proceedings of the First MICCAI Challenge on Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance, LISA 2024, Held in Conjunction with MICCAI 2024, in Marrakesh, Morocco, in October 2024. The 6 full papers p...
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| 格式: | Online |
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| 語言: | 英语 |
| 出版: |
Springer Nature
2025
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| 主題: | |
| 在線閱讀: | ONIX_20250313_9783031830082_47 |
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| _version_ | 1869785433403031552 |
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| collection | Directory of Open Access Books |
| description | This open access LNCS volume 15515 constitutes the refereed proceedings of the First MICCAI Challenge on Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance, LISA 2024, Held in Conjunction with MICCAI 2024, in Marrakesh, Morocco, in October 2024. The 6 full papers presented were carefully reviewed and selected from 8 submissions. This MICCAI Challenge focuses on the development and evaluation of automatic image analysis and machine learning algorithms and Ultra-low-field brain imaging has the potential to become a transformative tool for both clinical and research applications. |
| format | Online |
| id | doab-20.500.12854ir-157382 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Springer Nature |
| publisherStr | Springer Nature |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1573822026-07-04T05:12:14Z Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance Lepore, Natasha Linguraru, Marius George ultra low field magnetic resonance imaging pediatrics Quality assessment Automatic segmentation hippicampi deep leanring feature learning dual-view learning frequency masking classification thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning This open access LNCS volume 15515 constitutes the refereed proceedings of the First MICCAI Challenge on Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance, LISA 2024, Held in Conjunction with MICCAI 2024, in Marrakesh, Morocco, in October 2024. The 6 full papers presented were carefully reviewed and selected from 8 submissions. This MICCAI Challenge focuses on the development and evaluation of automatic image analysis and machine learning algorithms and Ultra-low-field brain imaging has the potential to become a transformative tool for both clinical and research applications. 2025-03-14T22:03:41Z 2025-03-14T22:03:41Z 2025-03-13T10:11:32Z 2025 book ONIX_20250313_9783031830082_47 https://library.oapen.org/handle/20.500.12657/99927 9783031830082 9783031830105 https://directory.doabooks.org/handle/20.500.12854/157382 eng Lecture Notes in Computer Science open access image/jpeg image/jpeg image/jpeg image/jpeg n/a n/a n/a n/a https://library.oapen.org/bitstream/20.500.12657/99927/1/9783031830082.pdf https://library.oapen.org/bitstream/20.500.12657/99927/1/9783031830082.pdf https://library.oapen.org/bitstream/20.500.12657/99927/1/9783031830082.pdf https://library.oapen.org/bitstream/20.500.12657/99927/1/9783031830082.pdf Springer Nature Springer Nature Switzerland 10.1007/978-3-031-83008-2 10.1007/978-3-031-83008-2 9fa3421d-f917-4153-b9ab-fc337c396b5a Bill & Melinda Gates Foundation Wellcome 054b013d-2433-4b19-a486-4f04be07bee8 9783031830082 9783031830105 Wellcome Springer Nature Switzerland 77 Cham [...] open access |
| spellingShingle | ultra low field magnetic resonance imaging pediatrics Quality assessment Automatic segmentation hippicampi deep leanring feature learning dual-view learning frequency masking classification thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance |
| title | Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance |
| title_full | Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance |
| title_fullStr | Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance |
| title_full_unstemmed | Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance |
| title_short | Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance |
| title_sort | low field pediatric brain magnetic resonance image segmentation and quality assurance |
| topic | ultra low field magnetic resonance imaging pediatrics Quality assessment Automatic segmentation hippicampi deep leanring feature learning dual-view learning frequency masking classification thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning |
| topic_facet | ultra low field magnetic resonance imaging pediatrics Quality assessment Automatic segmentation hippicampi deep leanring feature learning dual-view learning frequency masking classification thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning |
| url | ONIX_20250313_9783031830082_47 |