Deep auto-context convolutional neural networks for standard-dose PET image estimation from low-dose PET/MRI

Volume: 267, Pages: 406 - 416
Published: Dec 1, 2017
Abstract
Positron emission tomography (PET) is an essential technique in many clinical applications such as tumor detection and brain disorder diagnosis. In order to obtain high-quality PET images, a standard-dose radioactive tracer is needed, which inevitably causes the risk of radiation exposure damage. For reducing the patient's exposure to radiation and maintaining the high quality of PET images, in this paper, we propose a deep learning architecture...
Paper Details
Title
Deep auto-context convolutional neural networks for standard-dose PET image estimation from low-dose PET/MRI
Published Date
Dec 1, 2017
Volume
267
Pages
406 - 416
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.