no code implementations • 21 Nov 2021 • Qing Zou, Abdul Haseeb Ahmed, Prashant Nagpal, Sarv Priya, Rolf F Schulte, Mathews Jacob
Free-breathing cardiac MRI schemes are emerging as competitive alternatives to breath-held cine MRI protocols, enabling applicability to pediatric and other population groups that cannot hold their breath.
no code implementations • 30 Jun 2021 • Abdul Haseeb Ahmed, Prashant Nagpal, Mathews Jacob
Bilinear models that decompose dynamic data to spatial and temporal factors are powerful and memory-efficient tools for the recovery of dynamic MRI data.
no code implementations • 29 Jan 2021 • Qing Zou, Abdul Haseeb Ahmed, Prashant Nagpal, Stanley Kruger, Mathews Jacob
Unlike the popular CNN approaches that require extensive fully-sampled training data that is not available in this setting, the parameters of the CNN generator as well as the latent vectors are jointly estimated from the undersampled measurements using stochastic gradient descent.
no code implementations • 29 Jan 2021 • Qing Zou, Abdul Haseeb Ahmed, Prashant Nagpal, Stanley Kruger, Mathews Jacob
The proposed scheme brings in the spatial regularization provided by the convolutional network.
no code implementations • 20 Jan 2021 • Qing Zou, Abdul Haseeb Ahmed, Prashant Nagpal, Sarv Priya, Rolf Schulte, Mathews Jacob
Most of the current self-gating and manifold cardiac MRI approaches consider the independent recovery of images from each slice; these methods are not capable of exploiting the inter-slice redundancies in the datasets and require sophisticated post-processing or manual approaches to align the images from different slices.
2 code implementations • 16 Jan 2019 • Abdul Haseeb Ahmed, Yasir Mohsin, Ruixi Zhou, Yang Yang, Michael Salerno, Prashant Nagpal, Mathews Jacob
An iterative kernel low-rank algorithm is introduced to estimate the manifold structure of the images, or equivalently the manifold Laplacian matrix, from the central k-space regions.