“第四十九章 AI增强显微镜”版本间的差异
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第9行: | 第9行: | ||
==扩展阅读== | ==扩展阅读== | ||
− | * AI100问: 机器学习如何提高显微图像的质量 ? [http://aigraph.cslt.org/ | + | * AI100问: 机器学习如何提高显微图像的质量 ? [http://aigraph.cslt.org/ai100/AI-100-98-机器学习如何帮助生物学家提高显微图像质量.pdf] |
− | * 荧光显微镜 [ | + | * 维基百科 荧光显微镜 [http://aigraph.cslt.org/courses/49/熒光顯微鏡.pdf] |
− | + | * 增强现实(AR)显微镜助力病理AI实时检测癌症 [https://www.163.com/dy/article/EMI561J505329HWW.html] | |
+ | * AI+AR+医疗行业结合的案例典范:增强现实显微镜 [https://zhuanlan.zhihu.com/p/55993275] | ||
+ | * Google ARM [*][https://ai.googleblog.com/2018/04/an-augmented-reality-microscope.html] | ||
==视频展示== | ==视频展示== | ||
+ | * Google ARM [http://aigraph.cslt.org/courses/49/google-arm.mp4] | ||
+ | * Augmented Reality Microscopy [http://aigraph.cslt.org/courses/49/Augmented-Reality-Microscope.mp4] | ||
==演示链接== | ==演示链接== | ||
− | |||
==开发者资源== | ==开发者资源== | ||
− | * GVTNet source code [https://github.com/divelab/GVTNets] | + | * GVTNet source code [*] [https://github.com/divelab/GVTNets] |
==高级读者== | ==高级读者== | ||
* Nature collection: Deep learning in microscopy [https://www.nature.com/collections/cfcdjceech/] | * Nature collection: Deep learning in microscopy [https://www.nature.com/collections/cfcdjceech/] | ||
* Wang, Z., Xie, Y. & Ji, S. Global voxel transformer networks for augmented microscopy. Nat Mach Intell 3, 161–171 (2021). [https://doi.org/10.1038/s42256-020-00283-x] | * Wang, Z., Xie, Y. & Ji, S. Global voxel transformer networks for augmented microscopy. Nat Mach Intell 3, 161–171 (2021). [https://doi.org/10.1038/s42256-020-00283-x] | ||
+ | * Chen P H C, Gadepalli K, MacDonald R, et al. An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis[J]. Nature medicine, 2019, 25(9): 1453-1457. [https://www.nature.com/articles/s41591-019-0539-7?sf218127768=1] |
2023年8月13日 (日) 03:16的最后版本
教学资料
扩展阅读
- AI100问: 机器学习如何提高显微图像的质量 ? [2]
- 维基百科 荧光显微镜 [3]
- 增强现实(AR)显微镜助力病理AI实时检测癌症 [4]
- AI+AR+医疗行业结合的案例典范:增强现实显微镜 [5]
- Google ARM [*][6]
视频展示
演示链接
开发者资源
- GVTNet source code [*] [9]
高级读者
- Nature collection: Deep learning in microscopy [10]
- Wang, Z., Xie, Y. & Ji, S. Global voxel transformer networks for augmented microscopy. Nat Mach Intell 3, 161–171 (2021). [11]
- Chen P H C, Gadepalli K, MacDonald R, et al. An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis[J]. Nature medicine, 2019, 25(9): 1453-1457. [12]