Patch-CNN: Training data-efficient deep learning for high-fidelity diffusion tensor estimation from minimal diffusion protocols

no code implementations • 3 Jul 2023 • Tobias Goodwin-Allcock, Ting Gong, Robert Gray, Parashkev Nachev, HUI ZHANG

To overcome these limitations, we propose Patch-CNN, a neural network with a minimal (non-voxel-wise) convolutional kernel (3$\times$3$\times$3).

How can spherical CNNs benefit ML-based diffusion MRI parameter estimation?

no code implementations • 1 Jul 2022 • Tobias Goodwin-Allcock, Jason McEwen, Robert Gray, Parashkev Nachev, HUI ZHANG

A possible consequence of the lack of rotational equivariance is that the training dataset must contain a diverse range of microstucture orientations.