Results 261 to 270 of about 1,273,082 (321)
Risk analysis of the Unity 1.5T MR‐Linac adapt‐to‐shape workflow
Abstract Background and Purpose The adapt‐to‐shape (ATS) workflow on the Unity MR‐Linac (Elekta AB, Stockholm, Sweden) allows for full replanning including recontouring and reoptimization5. Additional complexity to this workflow is added when the adaptation involves the use of MIM Maestro (MIM Software, Cleveland, OH) software in conjunction with ...
Jiayi Liang+13 more
wiley +1 more source
Using deep learning generated CBCT contours for online dose assessment of prostate SABR treatments
Abstract Prostate Stereotactic Ablative Body Radiotherapy (SABR) is an ultra‐hypofractionated treatment where small setup errors can lead to higher doses to organs at risk (OARs). Although bowel and bladder preparation protocols reduce inter‐fraction variability, inconsistent patient adherence still results in OAR variability.
Conor Sinclair Smith+8 more
wiley +1 more source
Purpose Linear accelerator (LINAC)‐based single‐isocenter multi‐target (SIMT) treatment has streamlined the cranial stereotactic radiosurgery (SRS) workflow. Though efficient, SIMT delivery adds additional challenges that should be considered, including increased sensitivity to rotational errors for off‐isocenter targets.
Yohan A. Walter+4 more
wiley +1 more source
Semantic information, autonomous agency and non-equilibrium statistical physics. [PDF]
Kolchinsky A, Wolpert DH.
europepmc +1 more source
Abstract Purpose An evaluation of the accuracy, safety, and efficiency of the Halcyon ring delivery system (RDS) for stereotactic radiosurgery (SRS) treatment to relatively small (1–3 cm) brain lesions. Methods After completing the extensive in‐house quality assurance checks including Winston–Lutz test and independent dose verification via MD Anderson ...
Kate Hazelwood+5 more
wiley +1 more source
Statistical Challenges with Massive Datasets in Particle Physics
Bruce Knuteson, Paul Padley
openalex +1 more source
Blessing of dimensionality: mathematical foundations of the statistical physics of data. [PDF]
Gorban AN, Tyukin IY.
europepmc +1 more source
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