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Tyler J. Bradshaw
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Year
Deep learning MR imaging–based attenuation correction for PET/MR imaging
F Liu, H Jang, R Kijowski, T Bradshaw, AB McMillan
Radiology 286 (2), 676-684, 2018
4072018
Current methods to define metabolic tumor volume in positron emission tomography: which one is better?
HJ Im, T Bradshaw, M Solaiyappan, SY Cho
Nuclear medicine and molecular imaging 52, 5-15, 2018
2242018
A deep learning approach for 18F-FDG PET attenuation correction
F Liu, H Jang, R Kijowski, G Zhao, T Bradshaw, AB McMillan
EJNMMI physics 5, 1-15, 2018
1112018
Repeatability of quantitative 18F-NaF PET: a multicenter study
C Lin, T Bradshaw, T Perk, S Harmon, J Eickhoff, N Jallow, PL Choyke, ...
Journal of nuclear medicine 57 (12), 1872-1879, 2016
752016
Molecular imaging to plan radiotherapy and evaluate its efficacy
R Jeraj, T Bradshaw, U Simončič
Journal of Nuclear Medicine 56 (11), 1752-1765, 2015
682015
Nuclear medicine and artificial intelligence: best practices for algorithm development
TJ Bradshaw, R Boellaard, J Dutta, AK Jha, P Jacobs, Q Li, C Liu, A Sitek, ...
Journal of Nuclear Medicine 63 (4), 500-510, 2022
582022
Deep learning based MRAC using rapid ultrashort echo time imaging
H Jang, F Liu, G Zhao, T Bradshaw, AB McMillan
Medical physics 45 (8), 3697-3704, 2018
582018
Automated classification of benign and malignant lesions in 18F-NaF PET/CT images using machine learning
T Perk, T Bradshaw, S Chen, H Im, S Cho, S Perlman, G Liu, R Jeraj
Physics in Medicine & Biology 63 (22), 225019, 2018
522018
Feasibility of deep learning–based PET/MR attenuation correction in the pelvis using only diagnostic MR images
TJ Bradshaw, G Zhao, H Jang, F Liu, AB McMillan
Tomography 4 (3), 138-147, 2018
522018
Nuclear medicine and artificial intelligence: best practices for evaluation (the RELAINCE guidelines)
AK Jha, TJ Bradshaw, I Buvat, M Hatt, KC Prabhat, C Liu, NF Obuchowski, ...
Journal of Nuclear Medicine 63 (9), 1288-1299, 2022
502022
Joint EANM/SNMMI guideline on radiomics in nuclear medicine: Jointly supported by the EANM Physics Committee and the SNMMI Physics, Instrumentation and Data Sciences Council
M Hatt, AK Krizsan, A Rahmim, TJ Bradshaw, PF Costa, A Forgacs, ...
European Journal of Nuclear Medicine and Molecular Imaging 50 (2), 352-375, 2023
452023
Convolutional neural networks for automated PET/CT detection of diseased lymph node burden in patients with lymphoma
AJ Weisman, MW Kieler, SB Perlman, M Hutchings, R Jeraj, L Kostakoglu, ...
Radiology: Artificial Intelligence 2 (5), e200016, 2020
442020
Heterogeneity in intratumor correlations of 18F-FDG, 18F-FLT, and 61Cu-ATSM PET in canine sinonasal tumors
TJ Bradshaw, SR Bowen, N Jallow, LJ Forrest, R Jeraj
Journal of Nuclear Medicine 54 (11), 1931-1937, 2013
362013
Automated quantification of baseline imaging PET metrics on FDG PET/CT images of pediatric Hodgkin lymphoma patients
AJ Weisman, J Kim, I Lee, KM McCarten, S Kessel, CL Schwartz, KM Kelly, ...
EJNMMI physics 7, 1-12, 2020
322020
Comparison of 11 automated PET segmentation methods in lymphoma
AJ Weisman, MW Kieler, S Perlman, M Hutchings, R Jeraj, L Kostakoglu, ...
Physics in Medicine & Biology 65 (23), 235019, 2020
282020
Rapid dual‐echo ramped hybrid encoding MR‐based attenuation correction (d RHE‐MRAC) for PET/MR
H Jang, F Liu, T Bradshaw, AB McMillan
Magnetic resonance in medicine 79 (6), 2912-2922, 2018
282018
Molecular imaging biomarkers of resistance to radiation therapy for spontaneous nasal tumors in canines
TJ Bradshaw, SR Bowen, MA Deveau, L Kubicek, P White, SM Bentzen, ...
International Journal of Radiation Oncology* Biology* Physics 91 (4), 787-795, 2015
282015
Deep learning for classification of benign and malignant bone lesions in [F-18] NaF PET/CT images.
T Bradshaw, T Perk, S Chen, HJ Im, S Cho, S Perlman, R Jeraj
Journal of Nuclear Medicine 59 (supplement 1), 327-327, 2018
252018
Spatiotemporal stability of Cu-ATSM and FLT positron emission tomography distributions during radiation therapy
TJ Bradshaw, S Yip, N Jallow, LJ Forrest, R Jeraj
International Journal of Radiation Oncology* Biology* Physics 89 (2), 399-405, 2014
242014
Factors affecting the harmonization of disease-related metabolic brain pattern expression quantification in [18F] FDG-PET (PETMETPAT)
RV Kogan, BA de Jong, RJ Renken, SK Meles, PJH van Snick, S Golla, ...
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring 11, 472-482, 2019
192019
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