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First positronium imaging using $^{44}$Sc with the J-PET scanner: a case study on the NEMA-Image Quality phantom
Manish Das, Sushil Sharma, Aleksander Bilewicz, Jaros{\l}aw Choi\'nski, Neha Chug, Catalina Curceanu, Eryk Czerwi\'nski, Jakub Hajduga, Sharareh Jalali, Krzysztof Kacprzak, Tevfik Kaplanoglu, {\L}ukasz Kap{\l}on, Kamila Kasperska, Aleksander Khreptak, Grzegorz Korcyl, Tomasz Kozik, Karol Kubat, Deepak Kumar, Anoop Kunimmal Venadan, Edward Lisowski, Filip Lisowski, Ju…

First positronium imaging using $^{44}$Sc with the J-PET scanner: a case study on the NEMA-Image Quality phantom
Positronium Lifetime Imaging (PLI), an emerging extension of conventional positron emission tomography (PET) imaging, offers a novel window for probing the submolecular properties of biological tissues by imaging the mean lifetime of the positronium atom. Currently, the method is under rapid development in terms of reconstruction and detection systems. Recently, the first in vivo PLI of the human brain was performed using the J-PET scanner utilizing the $^{68}$Ga isotope. However, this isotope …

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2D PZT MEMS Resonant Scanner Using a Three-Mask Process
Mehrdad Khodapanahandeh, Parviz Zolfaghari, Hakan Urey
https://arxiv.org/abs/2505.24566 https://

2D PZT MEMS Resonant Scanner Using a Three-Mask Process
This work presents the design, simulation, fabrication, and characterization of a novel architectural compact two-dimensional (2D) resonant MEMS scanning mirror actuated by thin-film lead zirconate titanate (PZT). The device employs an innovative mechanically coupled dual-axis architecture fabricated using a three-mask process on an SOI-PZT deposited wafer, significantly reducing system complexity while achieving high performance. The scanner integrates a 1 $\times$ 1.4 mm oval mirror within a …

You can't hug your children with a computed tomography scanner.

wish I could find a single scanner app (as in using a flatbed, not my phone camera) that offered perspective crop instead of pretending that its auto skew fixing is flawless

A Privacy-Preserving Federated Learning Framework for Generalizable CBCT to Synthetic CT Translation in Head and Neck
Ciro Benito Raggio, Paolo Zaffino, Maria Francesca Spadea
https://arxiv.org/abs/2506.08654

A Privacy-Preserving Federated Learning Framework for Generalizable CBCT to Synthetic CT Translation in Head and Neck
Shortened Abstract Cone-beam computed tomography (CBCT) has become a widely adopted modality for image-guided radiotherapy (IGRT). However, CBCT suffers from increased noise, limited soft-tissue contrast, and artifacts, resulting in unreliable Hounsfield unit values and hindering direct dose calculation. Synthetic CT (sCT) generation from CBCT addresses these issues, especially using deep learning (DL) methods. Existing approaches are limited by institutional heterogeneity, scanner-dependent …

pyMEAL: A Multi-Encoder Augmentation-Aware Learning for Robust and Generalizable Medical Image Translation
Abdul-mojeed Olabisi Ilyas, Adeleke Maradesa, Jamal Banzi, Jianpan Huang, Henry K. F. Mak, Kannie W. Y. Chan
https://arxiv.org/abs/2505.24421

pyMEAL: A Multi-Encoder Augmentation-Aware Learning for Robust and Generalizable Medical Image Translation
Medical imaging is critical for diagnostics, but clinical adoption of advanced AI-driven imaging faces challenges due to patient variability, image artifacts, and limited model generalization. While deep learning has transformed image analysis, 3D medical imaging still suffers from data scarcity and inconsistencies due to acquisition protocols, scanner differences, and patient motion. Traditional augmentation uses a single pipeline for all transformations, disregarding the unique traits of each…

Epson Workforce Scanner bestellt und sofort zurück geschickt.
Grund: Gemäß Produktspezifikation kann er "Scannen zu FTP" das trifft aber nicht zu, er kann nur "Scannen zu Windows zu FTP".

Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction
George Webber, Alexander Hammers, Andrew P. King, Andrew J. Reader
https://arxiv.org/abs/2506.03804

Personalized MR-Informed Diffusion Models for 3D PET Image Reconstruction
Recent work has shown improved lesion detectability and flexibility to reconstruction hyperparameters (e.g. scanner geometry or dose level) when PET images are reconstructed by leveraging pre-trained diffusion models. Such methods train a diffusion model (without sinogram data) on high-quality, but still noisy, PET images. In this work, we propose a simple method for generating subject-specific PET images from a dataset of multi-subject PET-MR scans, synthesizing "pseudo-PET" images by transfor…

This https://arxiv.org/abs/2412.04339 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Likelihood-Scheduled Score-Based Generative Modeling for Fully 3D PET Image Reconstruction
Medical image reconstruction with pre-trained score-based generative models (SGMs) has advantages over other existing state-of-the-art deep-learned reconstruction methods, including improved resilience to different scanner setups and advanced image distribution modeling. SGM-based reconstruction has recently been applied to simulated positron emission tomography (PET) datasets, showing improved contrast recovery for out-of-distribution lesions relative to the state-of-the-art. However, existing…