Multi-Modal Image Registration with Unsupervised Deep Learning
https://dspace.mit.edu/handle/1721.1/123142 這篇論文主要是講多模配準的兩個損失函數MI和MIND，網絡結構還是voxelmorph。 摘要： 傳統的方法還是優化方法（optimization，只要是DL的方法都會這麼一說），所以很慢。 deep learning的方法是學習一個全局函數，加速配準過程。不過一般專注於單模配準。 引言： 不同的成像技術對體內
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相關文章
- 1. Multimodal Unsupervised Image-to-Image Translation
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