9 citations · 9 across the 1 of their papers we have counts for
5 papers
Model-based Reconstruction with Learning: From Unsupervised to Supervised and Beyond
Zhishen Huang, Siqi Ye, Michael T. McCann +1
Many techniques have been proposed for image reconstruction in medical imaging that aim to recover high-quality images especially from limited or corrupted measurements. Model-base…
Supervised Learning of Sparsity-Promoting Regularizers for Denoising
Michael T. McCann, Saiprasad Ravishankar
We present a method for supervised learning of sparsity-promoting regularizers for image denoising. Sparsity-promoting regularization is a key ingredient in solving modern image re…
Biomedical Image Reconstruction: From the Foundations to Deep Neural Networks
Michael T. McCann, Michael Unser
This tutorial covers biomedical image reconstruction, from the foundational concepts of system modeling and direct reconstruction to modern sparsity and learning-based approaches.…
Fast Rotational Sparse Coding
Michael T. McCann, Vincent Andrearczyk, Michael Unser +1
We propose an algorithm for rotational sparse coding along with an efficient implementation using steerability. Sparse coding (also called dictionary learning) is an important tech…
Rotation Invariant Angular Descriptor Via A Bandlimited Gaussian-like Kernel
Michael T. McCann, Matthew Fickus, Jelena Kovacevic
We present a new smooth, Gaussian-like kernel that allows the kernel density estimate for an angular distribution to be exactly represented by a finite number of its Fourier series…