Results 261 to 270 of about 709,545 (374)

Automatic skin flash optimization in breast and chestwall VMAT with static angle modulated ports: Effect of HU and flash margin size on plan quality and robustness

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Skin flash is typically added to breast and chestwall plans to ensure robust target coverage in the presence of respiratory motion, anatomic changes, and small setup uncertainties. Adding skin flash in volumetric modulated arc therapy (VMAT) plans is an iterative and manual process.
Emily Hubley   +6 more
wiley   +1 more source

Impact of enhanced leaf model on dose calculation accuracy in single‐isocenter multitarget stereotactic radiosurgery treatments

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Single‐isocenter multitarget (SIMT) radiosurgery has become increasingly popular as advancement in planning and delivery systems have made this approach clinically viable. With targets varying in size and distance from isocenter, SIMT plans are highly complex with dynamic multileaf collimator (MLC) motion.
Hem Moktan   +3 more
wiley   +1 more source

Commentary: Definitely maybe: can unconscious processes perform the same functions as conscious processes?

open access: yesFrontiers in Psychology, 2017
Ariel Goldstein   +2 more
doaj   +1 more source

Closing the gap in plan quality: Leveraging deep‐learning dose prediction for adaptive radiotherapy

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Balancing quality and efficiency has been a challenge for online adaptive therapy. Most systems start the online re‐optimization with the original planning goals. While some systems allow planners to modify the planning goals, achieving a high‐quality plan within time constraints remains a common barrier.
Sean J. Domal   +9 more
wiley   +1 more source

Alston\u27s Parity Thesis

open access: yes, 1993
McLeod, Mark S.
core  

A comparative analysis of deep learning architectures with data augmentation and multichannel input for locoregional breast cancer radiotherapy

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Studies on deep learning dose prediction increasingly focus on 3D models with multiple input channels and data augmentation, which increases the training time and thus also the environmental burden and hampers the ease of re‐training. Here we compare 2D and 3D U‐Net models with clinical accepted plans to evaluate the appropriateness of
Rosalie Klarenberg   +2 more
wiley   +1 more source

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