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A Unifying Multi-sampling-ratio CS-MRI Framework With Two-grid-cycle Correction and Geometric Prior Distillation [article]

Xiaohong Fan, Yin Yang, Ke Chen, Jianping Zhang, Ke Dong
2022 arXiv   pre-print
In this work, to tackle explainability and generalizability, we propose a unifying deep unfolding multi-sampling-ratio CS-MRI framework, by merging advantages of model-based and deep learning-based methods  ...  Although existing deep learning CS-MRI methods have achieved considerably impressive performance, explainability and generalizability continue to be challenging for such methods since most of them are  ...  These models can be effective for improvements of deep learning models, and in particular for the mathematical understanding and analysis of network architecture.  ... 
arXiv:2205.07062v1 fatcat:xhnnu2zatjepnjaw6xv6twt2qa

Large scale neuronal recording

Tim Blanche
Optimal methods of spike detection and sorting were explored in chapter 3 using real and simulated data.  ...  Chapter 1 describes the design and testing of high density,' 54-site polytrodes, and their use in multiunit studies of cat visual cortex.  ...  This may prove particularly useful for chronic studies of the neural correlates of perceptual and motor learning (eg.  ... 
doi:10.14288/1.0092344 fatcat:uw7an2v35varrj2rcxau3rmq5u