Frank J. Brooks

According to our database, Frank J. Brooks authored at least 15 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

Assessing the Ability of Generative Adversarial Networks to Learn Canonical Medical Image Statistics.

Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Prabhat K. C., Kyle J. Myers, Rongping Zeng, Mark A. Anastasio

IEEE Trans. Medical Imaging, June, 2023

Assessing the capacity of a denoising diffusion probabilistic model to reproduce spatial context.

Rucha Deshpande, Muzaffer Özbey, Hua Li, Mark A. Anastasio, Frank J. Brooks

CoRR, 2023

Evaluating generative stochastic image models using task-based image quality measures.

Varun A. Kelkar, Dimitrios S. Gotsis, Rucha Deshpande, Frank J. Brooks, Prabhat K. C., Kyle J. Myers, Rongping Zeng, Mark A. Anastasio

Proceedings of the Medical Imaging 2023: Image Perception, 2023

2022

Investigating the robustness of a learning-based method for quantitative phase retrieval from propagation-based x-ray phase contrast measurements under laboratory conditions.

Rucha Deshpande, Ashish Avachat, Frank J. Brooks, Mark A. Anastasio

CoRR, 2022

Evaluating procedures for establishing generative adversarial network-based stochastic image models in medical imaging.

Varun A. Kelkar, Dimitrios S. Gotsis, Frank J. Brooks, Kyle J. Myers, Prabhat K. C., Rongping Zeng, Mark A. Anastasio

Proceedings of the Medical Imaging 2022: Image Perception, 2022

Evaluating the capacity of deep generative models to reproduce measurable high-order spatial arrangements in diagnostic images.

Rucha Deshpande, Mark A. Anastasio, Frank J. Brooks

Proceedings of the Medical Imaging 2022: Image Processing, 2022

2021

On Hallucinations in Tomographic Image Reconstruction.

Sayantan Bhadra, Varun A. Kelkar, Frank J. Brooks, Mark A. Anastasio

IEEE Trans. Medical Imaging, 2021

A Method for Evaluating the Capacity of Generative Adversarial Networks to Reproduce High-order Spatial Context.

Rucha Deshpande, Mark A. Anastasio, Frank J. Brooks

CoRR, 2021

Learning stochastic object models from medical imaging measurements by use of advanced AmbientGANs.

Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio

CoRR, 2021

Advancing the AmbientGAN for learning stochastic object models.

Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Jason L. Granstedt, Hua Li, Mark A. Anastasio

Proceedings of the Medical Imaging 2021: Image Perception, 2021

Assessing regularization in tomographic imaging via hallucinations in the null space.

Sayantan Bhadra, Varun A. Kelkar, Frank J. Brooks, Mark A. Anastasio

Proceedings of the Medical Imaging 2021: Image Perception, 2021

2020

Learning stochastic object models from medical imaging measurements using Progressively-Growing AmbientGANs.

Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio

CoRR, 2020

Progressively-Growing AmbientGANs for learning stochastic object models from imaging measurements.

Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio

Proceedings of the Medical Imaging 2020: Image Perception, 2020

2019

Learning stochastic object model from noisy imaging measurements using AmbientGANs.

Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Mark A. Anastasio

Proceedings of the Medical Imaging 2019: Image Perception, 2019

2013

Quantification of heterogeneity observed in medical images.

Frank J. Brooks, Perry Grigsby

BMC Medical Imaging, 2013