Forming the image from a CAT scan and taking the blur out of vacation pictures are problems that are ill-posed. By definition, small changes in the data to an ill-posed problem make arbitrarily large changes in the solution. How can we hope to solve such problems when data are noisy and computer arithmetic is inexact?In this talk we discuss the ...
Creator:
O'Leary, Dianne P. (University of Maryland)
Created:
2011-06-06
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
This lecture gives an overview of methods for scan time reduction in quantitative MRI based on regularized image reconstruction. Besides the generic constraints that can be used for image series, the known signal model in quantitative MRI permits designing a model-based constraint tailored to the specific application. This is a much stronger pri...
Creator:
Doneva, Mariya (Philips Research Laboratory)
Created:
2019-10-14
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
In this talk, I will provide an introduction to the use of machine learning and convolutional neural networks (CNNs) in the area of MR image reconstruction. Building on a general framework of inverse problems and variational optimization, I will focus on application examples from image reconstruction for accelerated Magnetic Resonance (MR) imagi...
Creator:
Knoll, Florian (NYU Langone Medical Center)
Created:
2019-10-17
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
Ptychography comprises sampling and analyzing the object's spatial spectrogram by windowed (or "short-space") Fourier transforms. Its capability to reconstruct both image and illumination, as well as other experimental conditions including instabilities has proven promising for high-resolution X-ray microscopy. Practical implementation of X-ray ...
Creator:
Menzel, Andreas (Paul Scherrer Institute)
Created:
2017-08-14
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
