User profiles for Tyler J Bradshaw
Tyler J. BradshawAssistant Professor, University of Wisconsin - Madison Verified email at wisc.edu Cited by 1728 |
Nuclear medicine and artificial intelligence: best practices for evaluation (the RELAINCE guidelines)
An important need exists for strategies to perform rigorous objective clinical-task-based
evaluation of artificial intelligence (AI) algorithms for nuclear medicine. To address this need, we …
evaluation of artificial intelligence (AI) algorithms for nuclear medicine. To address this need, we …
Nuclear medicine and artificial intelligence: best practices for algorithm development
The nuclear medicine field has seen a rapid expansion of academic and commercial interest
in developing artificial intelligence (AI) algorithms. Users and developers can avoid some …
in developing artificial intelligence (AI) algorithms. Users and developers can avoid some …
A guide to cross-validation for artificial intelligence in medical imaging
Artificial intelligence (AI) is being increasingly used to automate and improve technologies
within the field of medical imaging. A critical step in the development of an AI algorithm is …
within the field of medical imaging. A critical step in the development of an AI algorithm is …
Convolutional neural networks for automated PET/CT detection of diseased lymph node burden in patients with lymphoma
…, R Jeraj, L Kostakoglu, TJ Bradshaw - Radiology: Artificial …, 2020 - pubs.rsna.org
Purpose To automatically detect lymph nodes involved in lymphoma on fluorine 18 ( 18 F)
fluorodeoxyglucose (FDG) PET/CT images using convolutional neural networks (CNNs). …
fluorodeoxyglucose (FDG) PET/CT images using convolutional neural networks (CNNs). …
Feasibility of deep learning–based PET/MR attenuation correction in the pelvis using only diagnostic MR images
This study evaluated the feasibility of using only diagnostically relevant magnetic resonance
(MR) images together with deep learning for positron emission tomography (PET)/MR …
(MR) images together with deep learning for positron emission tomography (PET)/MR …
[HTML][HTML] Automated quantification of baseline imaging PET metrics on FDG PET/CT images of pediatric Hodgkin lymphoma patients
…, CL Schwartz, KM Kelly, R Jeraj, SY Cho, TJ Bradshaw - EJNMMI physics, 2020 - Springer
Purpose For pediatric lymphoma, quantitative FDG PET/CT imaging features such as
metabolic tumor volume (MTV) are important for prognosis and risk stratification strategies. …
metabolic tumor volume (MTV) are important for prognosis and risk stratification strategies. …
Comparison of 11 automated PET segmentation methods in lymphoma
…, R Jeraj, L Kostakoglu, TJ Bradshaw - Physics in Medicine …, 2020 - iopscience.iop.org
Segmentation of lymphoma lesions in FDG PET/CT images is critical in both assessing
individual lesions and quantifying patient disease burden. Simple thresholding methods remain …
individual lesions and quantifying patient disease burden. Simple thresholding methods remain …
[PDF][PDF] Artificial Intelligence Algorithms Need to Be Explainable—or Do They?
With the growing role of artificial intelligence (AI) in radiology, there is concern over the black-box
nature of modern AI algorithms. Users of AI often have no way of knowing how or why …
nature of modern AI algorithms. Users of AI often have no way of knowing how or why …
Artificial intelligence–based data corrections for attenuation and scatter in position emission tomography and single-photon emission computed tomography
AB McMillan, TJ Bradshaw - PET clinics, 2021 - pet.theclinics.com
Both PET and single-photon emission computed tomography (SPECT) reconstructions require
several corrections to yield high-quality quantitative images. These corrections include …
several corrections to yield high-quality quantitative images. These corrections include …
Domain-adapted large language models for classifying nuclear medicine reports
…, C Lee, J Hu, SY Cho, TJ Bradshaw - Radiology: Artificial …, 2023 - pubs.rsna.org
Purpose To evaluate the impact of domain adaptation on the performance of language
models in predicting five-point Deauville scores on the basis of clinical fluorine 18 …
models in predicting five-point Deauville scores on the basis of clinical fluorine 18 …