Dr. Frank J. Brooks Profile

Dr. Frank J. Brooks

Research Assistant Professor at Univ of Illinois

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Author

Publications (15)

Proceedings Article | 30 March 2024 Presentation

Evaluating the capacity of a diffusion generative model to reproduce spatial context relevant to diagnostic imaging

Rucha Deshpande, Muzaffer Ozbey, Hua Li, Mark Anastasio, Frank Brooks

Proceedings Volume 12929, 129290I (2024) https://doi.org/10.1117/12.3006845

KEYWORDS: Diffusion, Diagnostics, Reproducibility, Anatomy, Performance modeling, Image quality, Stochastic processes, Gallium nitride

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Proceedings Article | 30 March 2024 Poster

Exploring a method to evaluate image-conditioned deep generative models for their capacity to reproduce domain-relevant spatial context

Rucha Deshpande, Mark Anastasio, Frank Brooks

Proceedings Volume 12929, 1292912 (2024) https://doi.org/10.1117/12.3006469

KEYWORDS: Particle filters, Reproducibility, Education and training, Biomedical optics, Visualization, Visual process modeling, Stochastic processes, Network architectures, Diagnostics, Design and modelling

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Proceedings Article | 7 April 2023 Poster

Assessing the applicability of a learning-based method for quantitative phase retrieval from propagation-based x-ray phase contrast images under benchtop conditions

Rucha Deshpande, Ashish Avachat, Frank Brooks, Mark Anastasio

Proceedings Volume 12463, 124632T (2023) https://doi.org/10.1117/12.2653921

KEYWORDS: Phase retrieval, X-rays, X-ray imaging, Phase contrast, Systems modeling, Spatial coherence, Data modeling

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Proceedings Article | 3 April 2023 Poster + Paper

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

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

Proceedings Volume 12467, 1246717 (2023) https://doi.org/10.1117/12.2654590

KEYWORDS: Signal detection, Image quality, Data modeling, Stochastic processes, Medical imaging, Medical statistics, Mammography, Image analysis, Realistic image synthesis

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Proceedings Article | 4 April 2022 Presentation + Paper

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

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

Proceedings Volume 12035, 120350O (2022) https://doi.org/10.1117/12.2612893

KEYWORDS: Machine learning, Medical imaging, Aneurysms, Computer simulations, Data modeling, Stochastic processes, Angiography, Visualization, Visual process modeling, Systems modeling

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Proceedings Article | 4 April 2022 Poster + Paper

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

Rucha Deshpande, Mark Anastasio, Frank Brooks

Proceedings Volume 12032, 120321X (2022) https://doi.org/10.1117/12.2611807

KEYWORDS: Diagnostics, Network architectures, Medical imaging, Feature extraction, Error analysis, Stochastic processes, Statistical modeling, Visualization

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SPIE Journal Paper | 16 March 2022 Open Access

Normalization of optical fluence distribution for three-dimensional functional optoacoustic tomography of the breast

Seonyeong Park, Frank Brooks, Umberto Villa, Richard Su, Mark Anastasio, Alexander Oraevsky

JBO, Vol. 27, Issue 03, 036001, (March 2022) https://doi.org/10.1117/12.10.1117/1.JBO.27.3.036001

KEYWORDS: Breast, Tissue optics, 3D image processing, Signal attenuation, Optoacoustics, Blood, 3D image reconstruction, Blood vessels, Imaging systems, Breast imaging

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SPIE Journal Paper | 23 February 2022 Open Access

Learning stochastic object models from medical imaging measurements by use of advanced ambient generative adversarial networks

Weimin Zhou, Sayantan Bhadra, Frank Brooks, Hua Li, Mark Anastasio

JMI, Vol. 9, Issue 01, 015503, (February 2022) https://doi.org/10.1117/12.10.1117/1.JMI.9.1.015503

KEYWORDS: Imaging systems, Medical imaging, Gallium nitride, Stochastic processes, Magnetic resonance imaging, Signal to noise ratio, Statistical modeling, Data acquisition, Systems modeling, Visualization

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Proceedings Article | 6 March 2021 Presentation

Three-dimensional quantitative functional optoacoustic tomography to estimate vascular blood oxygenation of the breast

Seonyeong Park, Umberto Villa, Frank Brooks, Richard Su, Alexander Oraevsky, Mark Anastasio

Proceedings Volume 11642, 116421N (2021) https://doi.org/10.1117/12.2585341

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The goal of quantitative optoacoustic tomography (qOAT) is to reconstruct a distribution of absolute chromophore concentrations and/or functional properties from measurements of the optically induced pressure (ultrasound signals) acquired at multiple excitation wavelengths. Estimating the distribution of hemoglobin, an endogenous OAT chromophore, is important because the oxygen saturation distribution of the blood vessels is a well-known indicator of aggressive growth of a cancerous tumor. In a number of studies, a spectral linear unmixing method has been applied to two-dimensional slices of tissue acquired with OAT at multiple wavelengths, leading to promising results at moderate penetration depths of ≤ 2 cm. In the three-dimensional (3D) OAT of the breast, such functional images cannot be accurately reconstructed via the spectral linear unmixing method due to unknown spatial distribution of the optical fluence in a relatively large size of the volume of interest (≥ 4 cm). Optical attenuation in biological tissue depends on the optical wavelength, and the optical fluence is exponentially attenuated with increasing imaging depth. Thus, the accuracy of the estimated distribution decreases with depth. To overcome this challenge, we investigated a spectral linear unmixing method with a simplified optical fluence normalization based on measurements of background absorbed optical energy in the breast. We compare estimates of blood oxygen saturations from two-wavelength clinical OAT breast images and demonstrate acceptable accuracy of ~10% while lack of compensation for the optical fluence distribution can lead to values outside the physiological range. We also quantitatively compare the accuracy of oxygen saturation estimates using numerical simulation of photon transport in realistic 3D OAT breast phantoms at dual wavelengths of 757 and 850 nm with inverse ratio of the optical absorption by deoxy- (Hb) and oxy-hemoglobin (HbO2) and three wavelengths of 757, 800, and 850 nm with inclusion of isosbestic point of the optical absorption in Hb/HbO₂.

Proceedings Article | 15 February 2021 Presentation + Paper

Advancing the AmbientGAN for learning stochastic object models

Weimin Zhou, Sayantan Bhadra, Frank Brooks, Jason Granstedt, Hua Li, Mark Anastasio

Proceedings Volume 11599, 115990A (2021) https://doi.org/10.1117/12.2581687

KEYWORDS: Systems modeling, Stochastic processes, Imaging systems, 3D image processing, Gallium nitride, 3D metrology, Stereoscopy, Network architectures, Medical imaging, Magnetic resonance imaging

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Proceedings Article | 15 February 2021 Presentation + Paper

Assessing regularization in tomographic imaging via hallucinations in the null space

Sayantan Bhadra, Varun Kelkar, Frank Brooks, Mark Anastasio

Proceedings Volume 11599, 115990N (2021) https://doi.org/10.1117/12.2581316

KEYWORDS: Tomography, Medical imaging, Magnetic resonance imaging, Inverse problems, Image restoration, Neural networks, Image analysis

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Proceedings Article | 16 March 2020 Presentation + Paper

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

Weimin Zhou, Sayantan Bhadra, Frank Brooks, Hua Li, Mark Anastasio

Proceedings Volume 11316, 113160Q (2020) https://doi.org/10.1117/12.2549610

KEYWORDS: Magnetic resonance imaging, Imaging systems, Signal detection, Stochastic processes, Neuroimaging, Brain, Data modeling, Systems modeling

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Proceedings Article | 6 March 2020 Presentation

Realistic three-dimensional optoacoustic tomography imaging trials using the VICTRE breast phantom of FDA (Conference Presentation)

Seonyeong Park, Umberto Villa, Richard Su, Alexander Oraevsky, Frank Brooks, Mark Anastasio

Proceedings Volume 11240, 112401H (2020) https://doi.org/10.1117/12.2552380

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Proceedings Article | 4 March 2019 Presentation + Paper

Learning stochastic object model from noisy imaging measurements using AmbientGANs

Weimin Zhou, Sayantan Bhadra, Frank Brooks, Mark Anastasio

Proceedings Volume 10952, 109520M (2019) https://doi.org/10.1117/12.2512633

KEYWORDS: Signal detection, Stochastic processes, Imaging systems, Radon transform, Image processing, Tomography, Statistical modeling

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Proceedings Article | 14 May 2018 Presentation

Development of computed phase-sensitive x-ray imaging technologies for pre-clinical science (Conference Presentation)

Mark Anastasio, Frank Brooks, Sergey Komarov, Yujia Chen, Weimin Zhou

Proceedings Volume 10632, 106320I (2018) https://doi.org/10.1117/12.2309429

KEYWORDS: X-ray imaging, X-ray technology, X-rays, Tissues, 3D image processing, Refractive index, Coherence imaging, Image acquisition, Tomography, In vivo imaging

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Showing 5 of 15 publications

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