Results 241 to 250 of about 1,344,795 (373)

Loschmidt echo for deformed Wigner matrices. [PDF]

open access: yesLett Math Phys
Erdős L, Henheik J, Kolupaiev O.
europepmc   +1 more source

JACMP 2020–2024

open access: yes
Journal of Applied Clinical Medical Physics, EarlyView.
Susan L. Richardson
wiley   +1 more source

Machine stability and dosimetry for ultra‐high dose rate FLASH radiotherapy human clinical protocol

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Background The FLASH effect, induced by ultra‐high dose rate (UHDR) irradiations, offers the potential to spare normal tissue while effectively treating tumors. It is important to achieve precise and accurate dose delivery and to establish reliable detector systems, particularly for clinical trials needed to help the clinical transfer of FLASH‐
Patrik Gonçalves Jorge   +9 more
wiley   +1 more source

On the Spectral Form Factor for Random Matrices. [PDF]

open access: yesCommun Math Phys, 2023
Cipolloni G, Erdős L, Schröder D.
europepmc   +1 more source

JACMP 2015 – 2019

open access: yes
Journal of Applied Clinical Medical Physics, EarlyView.
Per. H. Halvorsen
wiley   +1 more source

DICOM attribute manipulation tool: Easily change frame of reference, series instance, and SOP instance UID

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose In radiation oncology, the integration and registration of multiple imaging modalities is a crucial aspect of the diagnosis and treatment planning process. These images are often inherently registered, a useful feature in most cases, but possibly a hindrance when registration modifications are required.
Brian M. Anderson, Casey Bojechko
wiley   +1 more source

Unsupervised non‐small cell lung cancer tumor segmentation using cycled generative adversarial network with similarity‐based discriminator

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Background Tumor segmentation is crucial for lung disease diagnosis and treatment. Most existing deep learning‐based automatic segmentation methods rely on manually annotated data for network training. Purpose This study aims to develop an unsupervised tumor segmentation network smic‐GAN by using a similarity‐driven generative adversarial ...
Chengyijue Fang   +2 more
wiley   +1 more source

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