Cardiovascular medical image and analysis based on 3D vision: A comprehensive survey
With the rapid development of 3D vision and computer graphics technology, the way humans interact with the world has undergone significant transformations. 3D vision-related technologies have profoundly impacted the analysis of cardiovascular diseases (CVD) based on medical imaging diagnosis. In thi...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2024-12-01
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| Series: | Meta-Radiology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2950162824000560 |
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| author | Zhifeng Wang Renjiao Yi Xin Wen Chenyang Zhu Kai Xu |
| author_facet | Zhifeng Wang Renjiao Yi Xin Wen Chenyang Zhu Kai Xu |
| author_sort | Zhifeng Wang |
| collection | DOAJ |
| description | With the rapid development of 3D vision and computer graphics technology, the way humans interact with the world has undergone significant transformations. 3D vision-related technologies have profoundly impacted the analysis of cardiovascular diseases (CVD) based on medical imaging diagnosis. In this paper, we provide a comprehensive review of CVD analysis based on 3D vision. First, we delineate cardiovascular imaging and cardiovascular data types from both medical and computational perspectives. Then, we introduce a systematic taxonomy to comprehensively review the current practices of 3D vision in cardiovascular applications, covering aspects such as 3D vascular segmentation, 3D vascular map generation, 3D vascular reconstruction, and 3D vascular super-resolution. Additionally, we compile a list of publicly accessible cardiac image datasets and code repositories to support the reproduction of related algorithms and foster data and algorithm sharing within the community. Finally, we discuss the inherent challenges and limitations of cardiovascular imaging methods based on 3D vision and their potential and propose directions for overcoming these obstacles in future research. |
| format | Article |
| id | doaj-art-63d4b72a46e848da8382ebdc9cfbcad9 |
| institution | Kabale University |
| issn | 2950-1628 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Meta-Radiology |
| spelling | doaj-art-63d4b72a46e848da8382ebdc9cfbcad92025-01-04T04:57:33ZengKeAi Communications Co., Ltd.Meta-Radiology2950-16282024-12-0124100102Cardiovascular medical image and analysis based on 3D vision: A comprehensive surveyZhifeng Wang0Renjiao Yi1Xin Wen2Chenyang Zhu3Kai Xu4National University of Defense Technology, No. 109, Deya Road, Kaifu District, Changsha, 410073, Hunan, ChinaCorresponding author.; National University of Defense Technology, No. 109, Deya Road, Kaifu District, Changsha, 410073, Hunan, ChinaNational University of Defense Technology, No. 109, Deya Road, Kaifu District, Changsha, 410073, Hunan, ChinaNational University of Defense Technology, No. 109, Deya Road, Kaifu District, Changsha, 410073, Hunan, ChinaNational University of Defense Technology, No. 109, Deya Road, Kaifu District, Changsha, 410073, Hunan, ChinaWith the rapid development of 3D vision and computer graphics technology, the way humans interact with the world has undergone significant transformations. 3D vision-related technologies have profoundly impacted the analysis of cardiovascular diseases (CVD) based on medical imaging diagnosis. In this paper, we provide a comprehensive review of CVD analysis based on 3D vision. First, we delineate cardiovascular imaging and cardiovascular data types from both medical and computational perspectives. Then, we introduce a systematic taxonomy to comprehensively review the current practices of 3D vision in cardiovascular applications, covering aspects such as 3D vascular segmentation, 3D vascular map generation, 3D vascular reconstruction, and 3D vascular super-resolution. Additionally, we compile a list of publicly accessible cardiac image datasets and code repositories to support the reproduction of related algorithms and foster data and algorithm sharing within the community. Finally, we discuss the inherent challenges and limitations of cardiovascular imaging methods based on 3D vision and their potential and propose directions for overcoming these obstacles in future research.http://www.sciencedirect.com/science/article/pii/S2950162824000560CardiovascularMedical image and analysis3D visionSurvey |
| spellingShingle | Zhifeng Wang Renjiao Yi Xin Wen Chenyang Zhu Kai Xu Cardiovascular medical image and analysis based on 3D vision: A comprehensive survey Meta-Radiology Cardiovascular Medical image and analysis 3D vision Survey |
| title | Cardiovascular medical image and analysis based on 3D vision: A comprehensive survey |
| title_full | Cardiovascular medical image and analysis based on 3D vision: A comprehensive survey |
| title_fullStr | Cardiovascular medical image and analysis based on 3D vision: A comprehensive survey |
| title_full_unstemmed | Cardiovascular medical image and analysis based on 3D vision: A comprehensive survey |
| title_short | Cardiovascular medical image and analysis based on 3D vision: A comprehensive survey |
| title_sort | cardiovascular medical image and analysis based on 3d vision a comprehensive survey |
| topic | Cardiovascular Medical image and analysis 3D vision Survey |
| url | http://www.sciencedirect.com/science/article/pii/S2950162824000560 |
| work_keys_str_mv | AT zhifengwang cardiovascularmedicalimageandanalysisbasedon3dvisionacomprehensivesurvey AT renjiaoyi cardiovascularmedicalimageandanalysisbasedon3dvisionacomprehensivesurvey AT xinwen cardiovascularmedicalimageandanalysisbasedon3dvisionacomprehensivesurvey AT chenyangzhu cardiovascularmedicalimageandanalysisbasedon3dvisionacomprehensivesurvey AT kaixu cardiovascularmedicalimageandanalysisbasedon3dvisionacomprehensivesurvey |