Search Results for author: Katherine L. Bouman

Found 30 papers, 10 papers with code

Reconstructing Video from Interferometric Measurements of Time-Varying Sources

1 code implementation3 Nov 2017 Katherine L. Bouman, Michael D. Johnson, Adrian V. Dalca, Andrew A. Chael, Freek Roelofs, Sheperd S. Doeleman, William T. Freeman

Most recently, the Event Horizon Telescope (EHT) has extended VLBI to short millimeter wavelengths with a goal of achieving angular resolution sufficient for imaging the event horizons of nearby supermassive black holes.

Image Imputation Radio Interferometry

High Resolution Linear Polarimetric Imaging for the Event Horizon Telescope

1 code implementation19 May 2016 Andrew A. Chael, Michael D. Johnson, Ramesh Narayan, Sheperd S. Doeleman, John F. C. Wardle, Katherine L. Bouman

Polarimetric MEM is thus an attractive choice for image reconstruction with the

Instrumentation and Methods for Astrophysics Astrophysics of Galaxies

Dynamical Imaging with Interferometry

1 code implementation3 Nov 2017 Michael D. Johnson, Katherine L. Bouman, Lindy Blackburn, Andrew A. Chael, Julian Rosen, Hotaka Shiokawa, Freek Roelofs, Kazunori Akiyama, Vincent L. Fish, Sheperd S. Doeleman

By linking widely separated radio dishes, the technique of very long baseline interferometry (VLBI) can greatly enhance angular resolution in radio astronomy.

Instrumentation and Methods for Astrophysics

Interferometric Imaging Directly with Closure Phases and Closure Amplitudes

1 code implementation19 Mar 2018 Andrew A. Chael, Michael D. Johnson, Katherine L. Bouman, Lindy L. Blackburn, Kazunori Akiyama, Ramesh Narayan

Closure-only imaging provides results that are as non-committal as possible and allows for reconstructing an image independently from separate amplitude and phase self-calibration.

Instrumentation and Methods for Astrophysics High Energy Astrophysical Phenomena

alpha-Deep Probabilistic Inference (alpha-DPI): efficient uncertainty quantification from exoplanet astrometry to black hole feature extraction

1 code implementation21 Jan 2022 He Sun, Katherine L. Bouman, Paul Tiede, Jason J. Wang, Sarah Blunt, Dimitri Mawet

Inferring the posterior of hidden features, conditioned on the observed measurements, is essential for understanding the uncertainty of results and downstream scientific interpretations.

Uncertainty Quantification Variational Inference

End-to-End Sequential Sampling and Reconstruction for MRI

1 code implementation13 May 2021 Tianwei Yin, Zihui Wu, He Sun, Adrian V. Dalca, Yisong Yue, Katherine L. Bouman

In this paper, we leverage the sequential nature of MRI measurements, and propose a fully differentiable framework that jointly learns a sequential sampling policy simultaneously with a reconstruction strategy.

Medical Image Imputation from Image Collections

2 code implementations17 Aug 2018 Adrian V. Dalca, Katherine L. Bouman, William T. Freeman, Natalia S. Rost, Mert R. Sabuncu, Polina Golland

We present an algorithm for creating high resolution anatomically plausible images consistent with acquired clinical brain MRI scans with large inter-slice spacing.

Anatomy Image Imputation +2

Measurement-Robust Control Barrier Functions: Certainty in Safety with Uncertainty in State

1 code implementation28 Apr 2021 Ryan K. Cosner, Andrew W. Singletary, Andrew J. Taylor, Tamas G. Molnar, Katherine L. Bouman, Aaron D. Ames

The increasing complexity of modern robotic systems and the environments they operate in necessitates the formal consideration of safety in the presence of imperfect measurements.

Multi-resolution Data Fusion for Super-Resolution Electron Microscopy

no code implementations28 Nov 2016 Suhas Sreehari, S. V. Venkatakrishnan, Katherine L. Bouman, Jeffrey P. Simmons, Lawrence F. Drummy, Charles A. Bouman

Consequently, there is an enormous demand in the materials and biological sciences to image at greater speed and lower dosage, while maintaining resolution.

Super-Resolution

Computational Imaging for VLBI Image Reconstruction

no code implementations CVPR 2016 Katherine L. Bouman, Michael D. Johnson, Daniel Zoran, Vincent L. Fish, Sheperd S. Doeleman, William T. Freeman

Very long baseline interferometry (VLBI) is a technique for imaging celestial radio emissions by simultaneously observing a source from telescopes distributed across Earth.

Image Reconstruction

Visual Dynamics: Stochastic Future Generation via Layered Cross Convolutional Networks

no code implementations24 Jul 2018 Tianfan Xue, Jiajun Wu, Katherine L. Bouman, William T. Freeman

We study the problem of synthesizing a number of likely future frames from a single input image.

Visual Vibrometry: Estimating Material Properties From Small Motion in Video

no code implementations CVPR 2015 Abe Davis, Katherine L. Bouman, Justin G. Chen, Michael Rubinstein, Fredo Durand, William T. Freeman

The estimation of material properties is important for scene understanding, with many applications in vision, robotics, and structural engineering.

Scene Understanding

Turning Corners Into Cameras: Principles and Methods

no code implementations ICCV 2017 Katherine L. Bouman, Vickie Ye, Adam B. Yedidia, Fredo Durand, Gregory W. Wornell, Antonio Torralba, William T. Freeman

We show that walls and other obstructions with edges can be exploited as naturally-occurring "cameras" that reveal the hidden scenes beyond them.

Learning a Probabilistic Strategy for Computational Imaging Sensor Selection

no code implementations23 Mar 2020 He Sun, Adrian V. Dalca, Katherine L. Bouman

In this paper, we demonstrate the approach in the context of a very-long-baseline-interferometry (VLBI) array design task, where sensor correlations and atmospheric noise present unique challenges.

Visual Vibration Tomography: Estimating Interior Material Properties from Monocular Video

no code implementations CVPR 2022 Berthy T. Feng, Alexander C. Ogren, Chiara Daraio, Katherine L. Bouman

We propose an approach that estimates heterogeneous material properties of an object from a monocular video of its surface vibrations.

Object

Unsupervised learning of MRI tissue properties using MRI physics models

no code implementations6 Jul 2021 Divya Varadarajan, Katherine L. Bouman, Andre van der Kouwe, Bruce Fischl, Adrian V. Dalca

In this work we propose an unsupervised deep-learning strategy that employs MRI physics to estimate all three tissue properties from a single multiecho MRI scan session, and generalizes across varying acquisition parameters.

Inference of Black Hole Fluid-Dynamics From Sparse Interferometric Measurements

no code implementations ICCV 2021 Aviad Levis, Daeyoung Lee, Joel A. Tropp, Charles F. Gammie, Katherine L. Bouman

We are motivated by the task of imaging the stochastically evolving environment surrounding black holes, and demonstrate how flow parameters can be estimated from sparse interferometric measurements used in radio astronomical imaging.

Gravitationally Lensed Black Hole Emission Tomography

no code implementations CVPR 2022 Aviad Levis, Pratul P. Srinivasan, Andrew A. Chael, Ren Ng, Katherine L. Bouman

In this work, we propose BH-NeRF, a novel tomography approach that leverages gravitational lensing to recover the continuous 3D emission field near a black hole.

3D Reconstruction

Image Reconstruction without Explicit Priors

no code implementations21 Mar 2023 Angela F. Gao, Oscar Leong, He Sun, Katherine L. Bouman

We show that such a set of inverse problems can be solved simultaneously by learning a shared image generator with a low-dimensional latent space.

Image Reconstruction

Discovering Structure From Corruption for Unsupervised Image Reconstruction

no code implementations12 Apr 2023 Oscar Leong, Angela F. Gao, He Sun, Katherine L. Bouman

We show that such a set of inverse problems can be solved simultaneously without the use of a spatial image prior by instead inferring a shared image generator with a low-dimensional latent space.

Denoising Image Reconstruction +1

Learning Task-Specific Strategies for Accelerated MRI

no code implementations25 Apr 2023 Zihui Wu, Tianwei Yin, Yu Sun, Robert Frost, Andre van der Kouwe, Adrian V. Dalca, Katherine L. Bouman

Traditional CS-MRI methods often separately address measurement subsampling, image reconstruction, and task prediction, resulting in a suboptimal end-to-end performance.

Image Reconstruction

Efficient Bayesian Computational Imaging with a Surrogate Score-Based Prior

no code implementations5 Sep 2023 Berthy T. Feng, Katherine L. Bouman

We propose a surrogate function for efficient use of score-based priors for Bayesian inverse imaging.

Variational Inference

Single View Refractive Index Tomography with Neural Fields

no code implementations8 Sep 2023 Brandon Zhao, Aviad Levis, Liam Connor, Pratul P. Srinivasan, Katherine L. Bouman

The effects of such fields appear in many scientific computer vision settings, ranging from refraction due to transparent cells in microscopy to the lensing of distant galaxies caused by dark matter in astrophysics.

3D Reconstruction

Orbital Polarimetric Tomography of a Flare Near the Sagittarius A* Supermassive Black Hole

no code implementations11 Oct 2023 Aviad Levis, Andrew A. Chael, Katherine L. Bouman, Maciek Wielgus, Pratul P. Srinivasan

One mechanism for observed flares is the formation of compact bright regions that appear within the accretion disk and close to the event horizon.

3D Reconstruction

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