5 papers
A deep learning framework for morphologic detail beyond the diffraction limit in infrared spectroscopic imaging
Kianoush Falahkheirkhah, Kevin Yeh, Shachi Mittal +2
Infrared (IR) microscopes measure spectral information that quantifies molecular content to assign the identity of biomedical cells but lack the spatial quality of optical microsco…
Composition-Aware Spectroscopic Tomography
Luke Pfister, Rohit Bhargava, Yoram Bresler +1
Chemical imaging provides information about the distribution of chemicals within a target. When combined with structural information about the target, in situ chemical imaging open…
Transform Learning for Magnetic Resonance Image Reconstruction: From Model-based Learning to Building Neural Networks
Bihan Wen, Saiprasad Ravishankar, Luke Pfister +1
Magnetic resonance imaging (MRI) is widely used in clinical practice, but it has been traditionally limited by its slow data acquisition. Recent advances in compressed sensing (CS)…
Learning Filter Bank Sparsifying Transforms
Luke Pfister, Yoram Bresler
Data is said to follow the transform (or analysis) sparsity model if it becomes sparse when acted on by a linear operator called a sparsifying transform. Several algorithms have be…
Bounding Multivariate Trigonometric Polynomials with Applications to Filter Bank Design
Luke Pfister, Yoram Bresler
The extremal values of multivariate trigonometric polynomials are of interest in fields ranging from control theory to filter design, but finding the extremal values of such a poly…