Results 181 to 190 of about 24,230 (259)

Application of Noise2Inverse and adaptation (Noise2Phase) to single‐mask x‐ray phase contrast micro‐computed tomography

Journal of Microscopy, EarlyView.
Abstract X‐ray phase contrast imaging (XPCI), when implemented in micro‐computed tomography (micro‐CT) mode, offers high‐contrast 3D imaging of weakly‐attenuating material samples. In the so‐called single‐mask edge illumination approach, a mask with periodically spaced transmitting apertures is used to split the x‐ray beam into narrow beamlets; when ...
Khushal Shah, Grammatiki Lioliou, Dai Chen, Alexander Denker, Peter Munro, Marco Endrizzi, Alberto Astolfo, Alessandro Olivo, Charlotte K. Hagen   +8 more
wiley   +1 more source

Research on Medical Image Super-Resolution Reconstruction Algorithm Based on Dilated Convolution and Multi-Module Fusion. [PDF]

J Imaging
Xu Z, Guo Y.
europepmc   +1 more source

3SD: Rotational symmetry single‐shot denoising in fluorescence microscopy

Journal of Microscopy, EarlyView.
Abstract Image noise is a fundamental problem in fluorescence microscopy analysis, especially in live cell imaging applications where the number of detected photons is limited due to low power of excitation lasers to prevent phototoxicity during extended imaging experiments.
Tijmen H. de Wolf, Pleun Engbers, Justine Perrin, Julie Nonnekens, Ihor Smal   +4 more
wiley   +1 more source

Localized Quadratic RF Encoded Spin‐Echo With Spiral‐PRIME Reconstruction: A Practical Alternative to 3D FSE for High‐Resolution Volumetric Brain MRI

Magnetic Resonance in Medicine, Volume 96, Issue 6, Page 2615-2628, December 2026.
ABSTRACT Purpose To extend localized quadratic (LQ) RF encoded spin‐echo imaging with acquisition and reconstruction strategies that improve efficiency and artifact robustness, positioning it as a practical alternative to 3D FSE for high‐resolution volumetric brain MRI.
Guruprasad Krishnamoorthy, Julia V. Velikina, James G. Pipe   +2 more
wiley   +1 more source

Three-dimensional animation compression optimization based on structured processing and adaptive spatiotemporal segmentation algorithm. [PDF]

PLoS One
Wang X, Yan X, Liu B, Liu K, Su Y.
europepmc   +1 more source

Training Deep Learning Based Dynamic MR Image Reconstruction Using Synthetic Fractals

Magnetic Resonance in Medicine, Volume 96, Issue 6, Page 2795-2802, December 2026.
ABSTRACT Purpose To investigate whether synthetically generated fractal data can be used to train deep learning (DL) models for dynamic MRI reconstruction, thereby avoiding the privacy, licensing, and availability limitations associated with cardiac MR training datasets.
Anirudh Raman, Olivier Jaubert, Mark Wrobel, Tina Yao, Ruaraidh Campbell, Rebecca R Baker, Ruta Virsinskaite, Daniel Knight, Michael Quail, Jennifer A Steeden, Vivek Muthurangu   +10 more
wiley   +1 more source

TAPGFusion: Anatomy-Aware Triple-Attention and MRI-Conditioned Prior Learning for Multimodal Medical Image Fusion. [PDF]

Biosensors (Basel)
Wang L, Zhou Y, Li W, Zhao J.
europepmc   +1 more source

An Open‐Source, Reproducible MRI Data Acquisition and Reconstruction Workflow Using Pulseq: Multi‐Site and Cross‐Vendor Validation

Magnetic Resonance in Medicine, Volume 96, Issue 6, Page 2721-2738, December 2026.
ABSTRACT Purpose Reproducibility in MRI is limited by variability in data acquisition, formatting, and reconstruction across sites and vendors. This work aimed to mitigate these challenges through an open‐source, vendor‐independent workflow originally developed for the 2023–24 ISMRM Repeat It with Me: Reproducibility Team Challenge.
Qingping Chen, Thomas H. M. Roos, Amaya Murguia, Yuhai Xie, Zheng Liu, Pengcheng Xu, Shohei Fujita, Sebastian Littin, Yogesh Rathi, Jiayu Zhu, Berkin Bilgic, Jon‐Fredrik Nielsen, Maxim Zaitsev   +12 more
wiley   +1 more source

A Review of Deep Learning Methods for Multimodal Medical Image Fusion. [PDF]

Sensors (Basel)
Shi Y, Rigou M.
europepmc   +1 more source

SMART: Speedy Measurement of Arabidopsis Rosette Traits

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Most computer vision‐ and machine learning‐based plant phenotyping systems compute traits such as shape and size rather than the color distribution of the plant surface, even though color can provide important insights into plant physiology. Therefore, we developed Speedy Measurement of Arabidopsis Rosette Traits (SMART), an open‐source plant ...
Suxing Liu, Allison E. Harris, Jiamei Li, Fiona L. Goggin, David G. Mendoza‐Cozatl, Alexander Bucksch   +5 more
wiley   +1 more source