Results 201 to 210 of about 5,912,088 (357)

The edge visualization metric: Quantifying the improvement of lung SBRT target definition with 4D CBCT

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Four‐dimensional cone‐beam CT (4D CBCT) incorporates oversampling of 3D data to reconstruct multi‐phase CBCT data sets representing distinct phases of the breathing cycle based on a diaphragmatic correlate of respiratory motion. Motion artifacts and blurring can be reduced relative to three‐dimensional cone‐beam (3D CBCT), allowing ...
Colton Baley   +4 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

A new metric for a metric space [PDF]

open access: yesProceedings of the American Mathematical Society, 1969
openaire   +1 more source

Enhanced analysis of gating latency in 0.35T MR‐linac through innovative time synchronization of a motion phantom and plastic scintillation detector

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose This study aims to evaluate how different gantry angles, breathing rates (BPM), cine image speeds, and tracking algorithms affect beam on/off latency and the subsequent impact on target dose for a 0.35T MR‐Linac with a 6 MV FFF beam.
Mateb Al Khalifa   +4 more
wiley   +1 more source

Data‐driven performance metrics for neural network learning

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView., 2023
Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri   +2 more
wiley   +1 more source

Energy dependence of the GAFCHROMIC LD‐V1 in the diagnostic radiographic modalities

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract The GAFCHROMIC LD‐V1 radiochromic film is widely used in dosimetry because it can provide high‐resolution two‐dimensional dose distributions without processing. This study aimed to evaluate the response characteristics at different effective energies, from the low‐energy range of mammography to the high‐energy range of computed tomography. Net
Tatsuhiro Gotanda   +9 more
wiley   +1 more source

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

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