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Michael Thompson McCann

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Publications associées (10)

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We present CryoGAN, a new paradigm for single-particle cryo-electron microscopy (cryo-EM) reconstruction based on unsupervised deep adversarial learning. In single-particle cryo-EM, the structure of a biomolecule needs to be reconstructed from a large set ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

This tutorial covers biomedical image reconstruction, from the foundational concepts of system modeling and direct reconstruction to modern sparsity and learning-based approaches. Imaging is a critical tool in biological research and medicine, and most ima ...

2019

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GlobalBioIm is an open-source MATLAB (R) library for solving inverse problems. The library capitalizes on the strong commonalities between forward models to standardize the resolution of a wide range of imaging inverse problems. Endowed with an operator-al ...

IOP PUBLISHING LTD2019

Region Of Interest X-Ray Computed Tomography Via Corrected Back Projection

Michaël Unser, Michael Thompson McCann, Laura Vilaclara

We present a new method for region of interest (ROI) reconstruction from high-resolution, nontruncated data in parallel-ray X-ray computed tomography (CT). Many of the approaches to ROI CT reconstruction in the literature rely on a costly forward projectio ...

IEEE2018

We propose a new, cost-efficient method for computing back projections in parallel-ray X-ray CT. Forward and back projections are the basis of almost all X-ray CT reconstruction methods, but computing these accurately is costly. In the special case of para ...

Institute of Electrical and Electronics Engineers2017

High-Quality Parallel-Ray x-Ray CT Back Projection Using Optimized Interpolation

Michaël Unser, Michael Thompson McCann

2017

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In this paper, we propose a novel deep convolutional neural network (CNN)-based algorithm for solving ill-posed inverse problems. Regularized iterative algorithms have emerged as the standard approach to ill-posed inverse problems in the past few decades. ...

2017

Convolutional Neural Networks for Inverse Problems in Imaging—A Review

Michaël Unser, Kyong Hwan Jin, Michael Thompson McCann

In this article, we review recent uses of convolutional neural networks (CNNs) to solve inverse problems in imaging. It has recently become feasible to train deep CNNs on large databases of images, and they have shown outstanding performance on object clas ...

IEEE2017

Slice-by-Slice versus Fully 3D Reconstruction for Parallel-Beam x-Ray Microtomography

Michaël Unser, Masih Nilchian, Michael Thompson McCann

We present a 3D iterative reconstruction method for microtomography, where iterative methods have previously been limited by their high computational cost. Our preliminary results show that it improves reconstruction quality over the traditional slice-by-s ...

OSA2016

Fast 3D reconstruction method for differential phase contrast X-ray CT

Michaël Unser, Masih Nilchian, Michael Thompson McCann, Marco Stampanoni

We present a fast algorithm for fully 3D regularized X-ray tomography reconstruction for both traditional and differential phase contrast measurements. In many applications, it is critical to reduce the X-ray dose while producing high-quality reconstructio ...

2016