UB Paderborn / Katalog / Suche / in CDI

1 – 25 von 274

Sortiert nach

DoseNet: a volumetric dose prediction algorithm using 3D fully-convolutional neural networks

Physics in medicine & biology, 2018-12, Vol.63 (23), p.235022-235022

2018

Volltextzugriff (PDF)

Single- and Multi-Fraction Stereotactic Radiosurgery Dose Tolerances of the Optic Pathways

International journal of radiation oncology, biology, physics, 2021-05, Vol.110 (1), p.87-99

2021

Volltextzugriff (PDF)

JACMP 2005–2009: Growth, quality, and opportunity

Journal of applied clinical medical physics, 2024-06, p.e14445

Solberg, Timothy D

2024

Volltextzugriff (PDF)

First Clinical Investigation of Cone Beam Computed Tomography and Deformable Registration for Adaptive Proton Therapy for Lung Cancer

International journal of radiation oncology, biology, physics, 2016-05, Vol.95 (1), p.549-559

2016

Volltextzugriff (PDF)

An unsupervised convolutional neural network-based algorithm for deformable image registration

Physics in medicine & biology, 2018-09, Vol.63 (18), p.185017-185017

2018

Volltextzugriff (PDF)

Conflict of interest and disclosure in healthcare: We can do better

Journal of applied clinical medical physics, 2023-05, Vol.24 (5), p.e14002-n/a

Solberg, Timothy D.

2023

Volltextzugriff (PDF)

Machine Learning in Radiation Oncology: Opportunities, Requirements, and Needs

Frontiers in oncology, 2018-04, Vol.8, p.110-110

2018

Volltextzugriff (PDF)

Governance in clinical academic medical school departments: A time for change

Journal of applied clinical medical physics, 2022-09, Vol.23 (9), p.e13767-n/a

Solberg, Timothy D.

2022

Volltextzugriff (PDF)

DoseGAN: a generative adversarial network for synthetic dose prediction using attention-gated discrimination and generation

Scientific reports, 2020-07, Vol.10 (1), p.11073-8, Article 11073

2020

Volltextzugriff (PDF)

Prompt gamma imaging for in vivo range verification of pencil beam scanning proton therapy

International journal of radiation oncology, biology, physics, 2017-09, Vol.99 (1), p.210-218

2017

Volltextzugriff (PDF)

Attention-enabled 3D boosted convolutional neural networks for semantic CT segmentation using deep supervision

Physics in medicine & biology, 2019-07, Vol.64 (13), p.135001-135001

2019

Volltextzugriff (PDF)

IMRT QA using machine learning: A multi‐institutional validation

Journal of applied clinical medical physics, 2017-09, Vol.18 (5), p.279-284

2017

Volltextzugriff (PDF)

Predicting radiation pneumonitis in locally advanced stage II–III non-small cell lung cancer using machine learning

Radiotherapy and oncology, 2019-04, Vol.133, p.106-112

2019

Volltextzugriff (PDF)

Using machine learning to predict radiation pneumonitis in patients with stage I non-small cell lung cancer treated with stereotactic body radiation therapy

Physics in medicine & biology, 2016-08, Vol.61 (16), p.6105-6120

2016

Volltextzugriff (PDF)

Deep nets vs expert designed features in medical physics: An IMRT QA case study

Medical physics (Lancaster), 2018-06, Vol.45 (6), p.2672-2680

2018

Volltextzugriff (PDF)

X-ray excited ZnS:Cu,Co afterglow nanoparticles for photodynamic activation

Applied physics letters, 2014-07, Vol.105 (1)

2014

Volltextzugriff (PDF)

Ex vivo validation of a stoichiometric dual energy CT proton stopping power ratio calibration

Physics in medicine & biology, 2018-03, Vol.63 (5), p.055016-055016

2018

Volltextzugriff (PDF)

Clinical decision support of radiotherapy treatment planning: A data-driven machine learning strategy for patient-specific dosimetric decision making

Radiotherapy and oncology, 2017-12, Vol.125 (3), p.392-397

2017

Volltextzugriff (PDF)

The application of artificial intelligence in the IMRT planning process for head and neck cancer

Oral oncology, 2018-12, Vol.87, p.111-116

2018

Volltextzugriff (PDF)

MediBoost: a Patient Stratification Tool for Interpretable Decision Making in the Era of Precision Medicine

Scientific reports, 2016-11, Vol.6 (1), p.37854-37854, Article 37854

2016

Volltextzugriff (PDF)

Expert-augmented machine learning

Proceedings of the National Academy of Sciences - PNAS, 2020-03, Vol.117 (9), p.4571-4577

2020

Volltextzugriff (PDF)

Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers

Medical physics (Lancaster), 2018-07, Vol.45 (7), p.3449-3459

2018

Volltextzugriff (PDF)

A Deep Look Into the Future of Quantitative Imaging in Oncology: A Statement of Working Principles and Proposal for Change

International journal of radiation oncology, biology, physics, 2018-11, Vol.102 (4), p.1074-1082

2018

Volltextzugriff (PDF)

Preoperative and postoperative prediction of long-term meningioma outcomes

PloS one, 2018-09, Vol.13 (9), p.e0204161-e0204161

2018

Volltextzugriff (PDF)

Building more accurate decision trees with the additive tree

Proceedings of the National Academy of Sciences - PNAS, 2019-10, Vol.116 (40), p.19887-19893

2019

Volltextzugriff (PDF)

1 – 25 von 274

Suche als RSS-Feed

Suchergebnisse filtern

Filter anzeigen

Nur zeigen

Geprüft (Peer-Review)
(245)
Mit Volltextzugriff
(242)

Publikationsform

1 weiteren anzeigen...

Weniger anzeigen...

Sprache

Englisch
(267)
Japanisch
(56)
Norwegisch
(1)
Somali
(1)

Erscheinungsjahr

n.n

Thema

Science & Technology
(185)
Life Sciences & Biomedicine
(175)
Humans
(127)
Radiology, Nuclear Medicine & Medical Imaging
(126)
Oncology
(69)
Male
(58)
Radiotherapy Dosage
(50)
Radiotherapy
(46)
Algorithms
(43)
Female
(43)
Dosimetry
(41)
Radiotherapy Planning, Computer-Assisted - Methods
(40)
Phantoms, Imaging
(37)
Biological And Medical Sciences
(35)
Radiation Therapy
(35)
Medical Sciences
(34)
Surgery
(28)
Aged
(27)
Middle Aged
(27)
Animals
(25)

15 weitere anzeigen...

Weniger anzeigen...

Neu hinzugefügt

... seit 30 Tagen
(2)
... seit 90 Tagen
(5)

Menü

Weitere Dienste

Einstellungen

DoseNet: a volumetric dose prediction algorithm using 3D fully-convolutional neural networks

Single- and Multi-Fraction Stereotactic Radiosurgery Dose Tolerances of the Optic Pathways

JACMP 2005–2009: Growth, quality, and opportunity

First Clinical Investigation of Cone Beam Computed Tomography and Deformable Registration for Adaptive Proton Therapy for Lung Cancer

An unsupervised convolutional neural network-based algorithm for deformable image registration

Conflict of interest and disclosure in healthcare: We can do better

Machine Learning in Radiation Oncology: Opportunities, Requirements, and Needs

Governance in clinical academic medical school departments: A time for change

DoseGAN: a generative adversarial network for synthetic dose prediction using attention-gated discrimination and generation

Prompt gamma imaging for in vivo range verification of pencil beam scanning proton therapy

Attention-enabled 3D boosted convolutional neural networks for semantic CT segmentation using deep supervision

IMRT QA using machine learning: A multi‐institutional validation

Predicting radiation pneumonitis in locally advanced stage II–III non-small cell lung cancer using machine learning

Using machine learning to predict radiation pneumonitis in patients with stage I non-small cell lung cancer treated with stereotactic body radiation therapy

Deep nets vs expert designed features in medical physics: An IMRT QA case study

X-ray excited ZnS:Cu,Co afterglow nanoparticles for photodynamic activation

Ex vivo validation of a stoichiometric dual energy CT proton stopping power ratio calibration

Clinical decision support of radiotherapy treatment planning: A data-driven machine learning strategy for patient-specific dosimetric decision making

The application of artificial intelligence in the IMRT planning process for head and neck cancer

MediBoost: a Patient Stratification Tool for Interpretable Decision Making in the Era of Precision Medicine

Expert-augmented machine learning

Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers

A Deep Look Into the Future of Quantitative Imaging in Oncology: A Statement of Working Principles and Proposal for Change

Preoperative and postoperative prediction of long-term meningioma outcomes

Building more accurate decision trees with the additive tree

Suchergebnisse filtern