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Recent work has shown improved lesion detectability and flexibility to reconstruction hyperparameters (e.g. scanner geometry or dose level) when PET images are reconstructed by leveraging pre-trained diffusion models. Such methods train a…

Medical Physics · Physics 2025-08-28 George Webber , Alexander Hammers , Andrew P. King , Andrew J. Reader

Score-based generative models (SGMs) have recently shown promising results for image reconstruction on simulated positron emission tomography (PET) datasets. In this work we have developed and implemented practical methodology for 3D image…

Determining the 3D structures of biological molecules is a key problem for both biology and medicine. Electron Cryomicroscopy (Cryo-EM) is a promising technique for structure estimation which relies heavily on computational methods to…

Machine Learning · Statistics 2015-01-29 Ali Punjani , Marcus A. Brubaker

Objective. Prompt-gamma imaging encompasses several approaches for online monitoring of beam range or deposited dose distribution in proton therapy. We test one of the imaging techniques - a coded mask approach - both experimentally and via…

Computed tomography (CT) relies on precise patient immobilization during image acquisition. Nevertheless, motion artifacts in the reconstructed images can persist. Motion compensation methods aim to correct such artifacts post-acquisition,…

Image and Video Processing · Electrical Eng. & Systems 2024-05-30 Mareike Thies , Fabian Wagner , Noah Maul , Siyuan Mei , Mingxuan Gu , Laura Pfaff , Nastassia Vysotskaya , Haijun Yu , Andreas Maier

Materials characterization remains a labor-intensive process, with a large amount of expert time required to post-process and analyze micrographs. As a result, machine learning has become an essential tool in materials science, including…

Materials Science · Physics 2024-03-20 Isaiah A. Moses , Chengyin Wu , Wesley F. Reinhart

In computed tomography (CT), the forward model consists of a linear Radon transform followed by an exponential nonlinearity based on the attenuation of light according to the Beer-Lambert Law. Conventional reconstruction often involves…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Sara Fridovich-Keil , Fabrizio Valdivia , Gordon Wetzstein , Benjamin Recht , Mahdi Soltanolkotabi

A single-particle cryo-electron microscopy (cryo-EM) measurement, called a micrograph, consists of multiple two-dimensional tomographic projections of a three-dimensional (3-D) molecular structure at unknown locations, taken under unknown…

Image and Video Processing · Electrical Eng. & Systems 2026-03-10 Shay Kreymer , Amit Singer , Tamir Bendory

CT images have been used to generate radiation therapy treatment plans for more than two decades. Dual-energy CT (DECT) has shown high accuracy in estimating electronic density or proton stopping-power maps used in treatment planning.…

Image and Video Processing · Electrical Eng. & Systems 2022-02-02 Tao Ge , Maria Medrano , Rui Liao , Jeffrey F. Williamson , David G. Politte , Bruce R. Whiting , Joseph A. O'Sullivan

Single particle cryo-electron microscopy has become a critical tool in structural biology over the last decade, able to achieve atomic scale resolution in three dimensional models from hundreds of thousands of (noisy) two-dimensional…

Numerical Analysis · Mathematics 2023-07-19 Aaditya V. Rangan , Leslie Greengard

The technique known as 4D-STEM has recently emerged as a powerful tool for the local characterization of crystalline structures in materials, such as cathode materials for Li-ion batteries or perovskite materials for photovoltaics. However,…

We introduce a framework for recovering an image from its rotationally and translationally invariant features based on autocorrelation analysis. This work is an instance of the multi-target detection statistical model, which is mainly used…

Image and Video Processing · Electrical Eng. & Systems 2022-03-03 Nicholas F. Marshall , Ti-Yen Lan , Tamir Bendory , Amit Singer

Direct reconstruction of positron emission tomography (PET) data using deep neural networks is a growing field of research. Initial results are promising, but often the networks are complex, memory utilization inefficient, produce…

Image and Video Processing · Electrical Eng. & Systems 2020-06-16 William Whiteley , Vladimir Panin , Chuanyu Zhou , Jorge Cabello , Deepak Bharkhada , Jens Gregor

Determining the three-dimensional structure of proteins and protein complexes at atomic resolution is a fundamental task in structural biology. Over the last decade, remarkable progress has been made using "single particle" cryo-electron…

Numerical Analysis · Mathematics 2017-06-05 Alex Barnett , Leslie Greengard , Andras Pataki , Marina Spivak

Modeling of the collimator-detector response (CDR) in SPECT reconstruction enables improved resolution and accuracy, and is thus important for quantitative imaging applications such as dosimetry. The implementation of CDR modeling, however,…

Positron Emission Tomography (PET) image reconstruction is inherently challenged by Poisson noise and physical degradation factors, which are further exacerbated in limited-angle acquisitions. While deep learning methods demonstrate…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Rüveyda Yilmaz , Yuli Wu , Johannes Stegmaier , Volkmar Schulz

Deep learning has significantly advanced PET image re-construction, achieving remarkable improvements in image quality through direct training on sinogram or image data. Traditional methods often utilize masks for inpainting tasks, but…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Bin Huang , Binzhong He , Yanhan Chen , Zhili Liu , Xinyue Wang , Binxuan Li , Qiegen Liu

Four-dimensional scanning transmission electron microscopy (4D-STEM) is one of the most rapidly growing modes of electron microscopy imaging. The advent of fast pixelated cameras and the associated data infrastructure have greatly…

Applications · Statistics 2019-08-27 Xin Li , Ondrej Dyck , Stephen Jesse , Andrew R. Lupini , Sergei V. Kalinin , Mark P. Oxley

In this work we consider the {\em image matching} problem for two grayscale $n \times n$ images, $M_1$ and $M_2$ (where pixel values range from 0 to 1). Our goal is to find an affine transformation $T$ that maps pixels from $M_1$ to pixels…

Data Structures and Algorithms · Computer Science 2011-11-09 Simon Korman , Daniel Reichman , Gilad Tsur

Near-future astronomical survey experiments, such as LSST, possess system requirements of unprecedented fidelity that span photometry, astrometry and shape transfer. Some of these requirements flow directly to the array of science imaging…

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