Results 211 to 220 of about 719,917 (315)

UR‐cycleGAN: Denoising full‐body low‐dose PET images using cycle‐consistent Generative Adversarial Networks

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose This study aims to develop a CycleGAN based denoising model to enhance the quality of low‐dose PET (LDPET) images, making them as close as possible to standard‐dose PET (SDPET) images. Methods Using a Philips Vereos PET/CT system, whole‐body PET images of fluorine‐18 fluorodeoxyglucose (18F‐FDG) were acquired from 37 patients to ...
Yang Liu, ZhiWu Sun, HaoJia Liu
wiley   +1 more source

Beam model development and clinical experience with RadCalc for treatment plan quality assurance in online adaptive workflow with an MR‐linac

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose The aim of this work was to report on the optimization, commissioning, and validation of a beam model using a commercial independent dose verification software RadCalc version 7.2 (Lifeline Software Inc, Tyler, TX, USA), along with 4 years of experience employing RadCalc for offline and online monitor unit (MU) verification on the ...
Urszula Jelen   +3 more
wiley   +1 more source

Indoor Segmentation and Support Inference from RGBD Images

open access: yesEuropean Conference on Computer Vision, 2012
N. Silberman   +3 more
semanticscholar   +1 more source

Accuracy and reproducibility of a single‐pose image‐to‐robot registration method for mobile C‐arm cone beam CT guided histotripsy

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Histotripsy is a focal tumor therapy that utilizes focused ultrasound (US) to mechanically destroy tissue. To overcome visualization limitations of diagnostic US‐guidance, C‐arm cone beam CT (CBCT)‐guided histotripsy is being developed, for which a mobile C‐arm could increase accessibility. CBCT‐guided histotripsy uses a phantom with a
Grace M. Minesinger   +5 more
wiley   +1 more source

Practical challenges in data‐driven interpolation: Dealing with noise, enforcing stability, and computing realizations

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView., 2023
Summary In this contribution, we propose a detailed study of interpolation‐based data‐driven methods that are of relevance in the model reduction and also in the systems and control communities. The data are given by samples of the transfer function of the underlying (unknown) model, that is, we analyze frequency‐response data.
Quirin Aumann, Ion Victor Gosea
wiley   +1 more source

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