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Maximum Entropy Image Reconstruction

IEEE Transactions on Computers, 1977
Two-dimensional digital image reconstruction is an important imaging process in many of the physical sciences. If the data are insufficient to specify a unique reconstruction, an additional criterion must be introduced, either implicitly or explicitly before the best estimate can be computed. Here we use a principle of maximum entropy, which has proven
Stephen J. Wernecke, Larry R. D'Addario
openaire   +2 more sources

Image Reconstruction by Multilabel Propagation

2017
This work presents a non-convex variational approach to joint image reconstruction and labeling. Our regularization strategy, based on the KL-divergence, takes into account the smooth geometry on the space of discrete probability distributions. The proposed objective function is efficiently minimized via DC programming which amounts to solving a ...
Zisler, Matthias   +3 more
openaire   +1 more source

Image Reconstruction in Optoacoustics.

2015
This thesis investigates reconstruction techniques for optoacoustic (oa) imaging, implemented both in pulsed and continuous wave (cw) mode. Two approaches to incorporate the transducer geometry into model-based reconstruction are implemented and its benefits showcased in simulations and experiments.
openaire   +2 more sources

AutoBCS: Block-Based Image Compressive Sensing With Data-Driven Acquisition and Noniterative Reconstruction

IEEE Transactions on Cybernetics, 2023
Chunyi Liu, Yang Gao, Hongping Gan
exaly  

On instabilities of deep learning in image reconstruction and the potential costs of AI

Proceedings of the National Academy of Sciences of the United States of America, 2020
Francesco Renna   +2 more
exaly  

Artificial Intelligence for MR Image Reconstruction: An Overview for Clinicians

Journal of Magnetic Resonance Imaging, 2021
Florian Knoll   +2 more
exaly  

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