T
Tyler Bradshaw
Researcher at University of Wisconsin-Madison
Publications - 55
Citations - 1151
Tyler Bradshaw is an academic researcher from University of Wisconsin-Madison. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 14, co-authored 41 publications receiving 767 citations. Previous affiliations of Tyler Bradshaw include University of Utah.
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Journal ArticleDOI
Deep Learning MR Imaging-based Attenuation Correction for PET/MR Imaging.
TL;DR: An automated approach that allows generation of discrete-valued pseudo CT scans from a single high-spatial-resolution diagnostic-quality three-dimensional MR image and evaluated it in brain PET/MR imaging provided reduced PET reconstruction error relative to a CT-based standard within the brain compared with current MR imaging-based AC approaches.
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Current Methods to Define Metabolic Tumor Volume in Positron Emission Tomography: Which One is Better?
TL;DR: This review discusses currently available methods to measure MTV using FDG PET, and assess the advantages and disadvantages of the methods.
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A deep learning approach for 18 F-FDG PET attenuation correction
TL;DR: An automated approach is developed that allows generation of a continuously valued pseudo-CT from a single 18F-FDG non-attenuation-corrected (NAC) PET image and evaluated it in PET/CT brain imaging and provides quantitatively accurate 18F -FDG PET results with average errors of less than 1% in most brain regions.
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Repeatability of quantitative 18F-NaF PET: A multicenter study
Christie Lin,Tyler Bradshaw,Timothy Perk,Stephanie Harmon,Jens C. Eickhoff,Ngoneh Jallow,Peter L. Choyke,William L. Dahut,Steven M. Larson,John L. Humm,Scott B. Perlman,Andrea B. Apolo,Michael J. Morris,Glenn Liu,Robert Jeraj +14 more
TL;DR: In this article, the authors evaluated the repeatability of 18F-NaF PET-derived SUV imaging metrics in individual bone lesions from patients in a multicenter study and found significant differences in lesion-level and patient-level distributions between sites.
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Molecular Imaging to Plan Radiotherapy and Evaluate Its Efficacy
TL;DR: Strong collaboration between radiation oncology, nuclear medicine/radiology, and medical physics teams is necessary, as optimal and safe use of molecular imaging can be ensured only within appropriate interdisciplinary teams.