Detalhe da pesquisa
1.
Automated tracking of morphologic changes in weekly magnetic resonance imaging during head and neck radiotherapy.
J Appl Clin Med Phys
; 24(7): e13959, 2023 Jul.
Artigo
em Inglês
| MEDLINE | ID: mdl-37147912
2.
Accuracy of surface-guided patient setup for conventional radiotherapy of brain and nasopharynx cancer.
J Appl Clin Med Phys
; 22(5): 48-57, 2021 May.
Artigo
em Inglês
| MEDLINE | ID: mdl-33792186
3.
Illustrated instructions for mechanical quality assurance of a medical linear accelerator.
J Appl Clin Med Phys
; 19(3): 355-359, 2018 May.
Artigo
em Inglês
| MEDLINE | ID: mdl-29500846
4.
Initial clinical experience with ArcCHECK for IMRT/VMAT QA.
J Appl Clin Med Phys
; 17(5): 20-33, 2016 09 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-27685107
5.
Artificial-intelligence-driven measurements of brain metastases' response to SRS compare favorably with current manual standards of assessment.
Neurooncol Adv
; 6(1): vdae015, 2024.
Artigo
em Inglês
| MEDLINE | ID: mdl-38464949
6.
Clinical Experience With an Offline Adaptive Radiation Therapy Head and Neck Program: Dosimetric Benefits and Opportunities for Patient Selection.
Int J Radiat Oncol Biol Phys
; 2024 Feb 17.
Artigo
em Inglês
| MEDLINE | ID: mdl-38373657
7.
Automatically tracking brain metastases after stereotactic radiosurgery.
Phys Imaging Radiat Oncol
; 27: 100452, 2023 Jul.
Artigo
em Inglês
| MEDLINE | ID: mdl-37720463
8.
A Potential Pitfall and Clinical Solutions in Surface-Guided Deep Inspiration Breath Hold Radiation Therapy for Left-Sided Breast Cancer.
Adv Radiat Oncol
; 8(6): 101276, 2023.
Artigo
em Inglês
| MEDLINE | ID: mdl-38047221
9.
3-D fiducial motion tracking using limited MV projections in arc therapy.
Med Phys
; 38(6): 3222-31, 2011 Jun.
Artigo
em Inglês
| MEDLINE | ID: mdl-21815397
10.
Automatic segmentation of brain metastases using T1 magnetic resonance and computed tomography images.
Phys Med Biol
; 66(17)2021 08 26.
Artigo
em Inglês
| MEDLINE | ID: mdl-34315148
11.
Deep learning auto-segmentation and automated treatment planning for trismus risk reduction in head and neck cancer radiotherapy.
Phys Imaging Radiat Oncol
; 19: 96-101, 2021 Jul.
Artigo
em Inglês
| MEDLINE | ID: mdl-34746452
12.
Use of a realistic breathing lung phantom to evaluate dose delivery errors.
Med Phys
; 37(11): 5850-7, 2010 Nov.
Artigo
em Inglês
| MEDLINE | ID: mdl-21158297
13.
Predictive dose accumulation for HN adaptive radiotherapy.
Phys Med Biol
; 65(23): 235011, 2020 11 27.
Artigo
em Inglês
| MEDLINE | ID: mdl-33007769
14.
Differences between planned and delivered dose for head and neck cancer, and their consequences for normal tissue complication probability and treatment adaptation.
Radiother Oncol
; 142: 100-106, 2020 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-31431381
15.
A PET Radiomics Model to Predict Refractory Mediastinal Hodgkin Lymphoma.
Sci Rep
; 9(1): 1322, 2019 02 04.
Artigo
em Inglês
| MEDLINE | ID: mdl-30718585
16.
The development and testing of a digital PET phantom for the evaluation of tumor volume segmentation techniques.
Med Phys
; 35(7): 3331-42, 2008 Jul.
Artigo
em Inglês
| MEDLINE | ID: mdl-18697557
17.
Evaluation of diffusion weighted imaging for tumor delineation in head-and-neck radiotherapy by comparison with automatically segmented 18F-fluorodeoxyglucose positron emission tomography.
Phys Imaging Radiat Oncol
; 5: 13-18, 2018 Jan.
Artigo
em Inglês
| MEDLINE | ID: mdl-33458363
18.
Deep-Inspiration Breath-Hold Intensity Modulated Radiation Therapy to the Mediastinum for Lymphoma Patients: Setup Uncertainties and Margins.
Int J Radiat Oncol Biol Phys
; 100(1): 254-262, 2018 01 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-29100788
19.
Auto-delineation of oropharyngeal clinical target volumes using 3D convolutional neural networks.
Phys Med Biol
; 63(21): 215026, 2018 11 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-30403188
20.
Omitting cardiophrenic lymph nodes in the treatment of patients with Hodgkin lymphoma via modified involved-site radiation therapy.
Leuk Lymphoma
; 59(11): 2650-2659, 2018 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-29616834