52.15.157.192=52.15
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&id=32621240&retmode=xml&tool=RemsenMedia&email=hello@remsenmedia.com&api_key=81853a771c3a3a2c6b2553a65bc33b056f0852.15.157.192=52.15
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&term=deep+learning&datetype=edat&usehistory=y&retmax=5&tool=RemsenMedia&email=hello@remsenmedia.com&api_key=81853a771c3a3a2c6b2553a65bc33b056f0852.15.157.192=52.15
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&WebEnv=MCID_67957aaa693100cfb50c8d2d&query_key=1&retmode=xml&retmax=5&tool=RemsenMedia&email=hello@remsenmedia.com&api_key=81853a771c3a3a2c6b2553a65bc33b056f08 From deep learning to dark fields-medical imaging physics in ECR 2020. | LitMetric
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From deep learning to dark fields-medical imaging physics in ECR 2020.

Mika Kortesniemi

Eur Radiol

HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, POB 340, FI-00029, Helsinki, Finland.

Published: December 2020

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http://dx.doi.org/10.1007/s00330-020-07045-8DOI Listing

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