David Paganin

Adjunct Professor (Research)

MONASH UNIVERSITY

Australia

Research Interests

Explore related searches

Professors in Australia Professors in Medical Imaging Medical Imaging professors in Australia

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

David Paganin is an Adjunct Professor (Research) at Monash University, Australia. His research areas encompass advanced imaging techniques, including high-resolution X-ray scanning, neutron beam shaping, and deep learning applications in X-ray ghost imaging. His recent publications explore topics such as X-ray dark-field imaging, the Transport-of-Intensity Equation for real-time tomographic experiments, and the optimization of X-ray zone plates.

Articles (21)

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

View details

Timothy Petersen

MONASH UNIVERSITY

AUSTRALIA

View details

Kaye Morgan

MONASH UNIVERSITY

AUSTRALIA

View details

Henning Friis Poulsen

Technical University of Denmark

DENMARK

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

David Paganin

Research Interests

Explore related searches

Contact this professor

About

Articles (21)

Separating edges from microstructure in X-ray dark-field imaging: evolving and devolving perspectives via the X-ray Fokker-Planck equation

High-resolution X-ray scanning with a diffuse Huffman-patterned probe to reduce radiation damage

Neutron beam shaping by ghost projection

Transport-of-Intensity Equation for Real-Time Tomographic Experiments: Projection or Slices?

Quantum and classical Fisher information in four-dimensional scanning transmission electron microscopy

Signal-to-noise and spatial resolution in in-line imaging. 1. Basic theory, numerical simulations and planar experimental images

Single-exposure elemental differentiation and texture-sensitive phase-retrieval imaging with a neutron-counting microchannel-plate detector

Optimum design of aspect ratio limited x-ray zone plates

X-ray phase and dark-field computed tomography without optical elements

Families of multi-level Legendre-like arrays

Deep learning in classical x-ray ghost imaging for dose reduction

Universal mask for hard x rays

Paraxial diffusion-field retrieval

Mask design, fabrication, and experimental ghost imaging applications for patterned X-ray illumination

X-Ray Dark-Field and Phase Retrieval Without Optics, via the Fokker–Planck Equation

Fast implicit diffusive dark-field retrieval for single-exposure, single-mask x-ray imaging

Revisiting Neutron Propagation-Based Phase-Contrast Imaging and Tomography: Use of Phase Retrieval to Amplify the Effective Degree of Brilliance

Optimizing nonconfigurable, transversely displaced masks for illumination patterns in classical ghost imaging

Attractor-driven matter

Ghost projection. II. Beam shaping using realistic spatially random masks

Shot-to-shot two-dimensional photon intensity diagnostics within megahertz pulse-trains at the European XFEL

Collaborators (8)

andrew kingston

Felix Hofmann

Lindon Roberts

Konstantin Pavlov

Rahil N. Valani

Timothy Petersen

Kaye Morgan

Henning Friis Poulsen

Make your next move.