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08/04/2023
Mechanistic Modeling and Analysis of Thermal Radiation in Conventional, Microwave-assisted, and Hybrid Freeze Drying for Biopharmaceutical Manufacturing
In freeze drying, thermal radiation has a significant effect on the dryi...
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08/02/2023
On the use of deep learning for phase recovery
Phase recovery (PR) refers to calculating the phase of the light field f...
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04/10/2023
Accelerated deep self-supervised ptycho-laminography for three-dimensional nanoscale imaging of integrated circuits
Three-dimensional inspection of nanostructures such as integrated circui...
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01/07/2023
The 3D Structural Phenotype of the Glaucomatous Optic Nerve Head and its Relationship with The Severity of Visual Field Damage
Purpose: To describe the 3D structural changes in both connective and ne...
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11/29/2022
Attentional Ptycho-Tomography (APT) for three-dimensional nanoscale X-ray imaging with minimal data acquisition and computation time
Noninvasive X-ray imaging of nanoscale three-dimensional objects, e.g. i...
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06/09/2022
AI-based Clinical Assessment of Optic Nerve Head Robustness Superseding Biomechanical Testing
𝐏𝐮𝐫𝐩𝐨𝐬𝐞: To use artificial intelligence (AI) to: (1) exploit biomechanic...
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04/14/2022
Geometric Deep Learning to Identify the Critical 3D Structural Features of the Optic Nerve Head for Glaucoma Diagnosis
Purpose: The optic nerve head (ONH) undergoes complex and deep 3D morpho...
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04/07/2022
Physics-assisted Generative Adversarial Network for X-Ray Tomography
X-ray tomography is capable of imaging the interior of objects in three ...
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11/15/2021
Advantage of Machine Learning over Maximum Likelihood in Limited-Angle Low-Photon X-Ray Tomography
Limited-angle X-ray tomography reconstruction is an ill-conditioned inve...
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07/21/2020
Limited-angle tomographic reconstruction of dense layered objects by dynamical machine learning
Limited-angle tomography of strongly scattering quasi-transparent object...
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04/14/2020
On the interplay between physical and content priors in deep learning for computational imaging
Deep learning (DL) has been applied extensively in many computational im...
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07/26/2019
Learning to Synthesize: Robust Phase Retrieval at Low Photon counts
The quality of inverse problem solutions obtained through deep learning ...
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11/19/2018
Learning to synthesize: splitting and recombining low and high spatial frequencies for image recovery
Deep Neural Network (DNN)-based image reconstruction, despite many succe...
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02/22/2017
Lensless computational imaging through deep learning
Deep learning has been proven to yield reliably generalizable answers to...
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07/09/2009
