Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis

  • Carole H. Sudre
  • Roxane Licandro
  • Christian Baumgartner
  • Andrew Melbourne
  • Adrian Dalca
  • Jana Hutter
  • Ryutaro Tanno
  • Esra Abaci Turk
  • Koen Van Leemput
  • Jordina Torrents Barrena
  • William M. Wells
  • Christopher Macgowan
Publisher:Springer NatureISBN 13: 9783030877354ISBN 10: 3030877353

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Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis is written by Carole H. Sudre and published by Springer Nature. It's available with International Standard Book Number or ISBN identification 3030877353 (ISBN 10) and 9783030877354 (ISBN 13).

This book constitutes the refereed proceedings of the Third International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2021, and the 6th International Workshop on Preterm, Perinatal and Paediatric Image Analysis, PIPPI 2021, held in conjunction with MICCAI 2021. The conference was planned to take place in Strasbourg, France, but was held virtually due to the COVID-19 pandemic.For UNSURE 2021, 13 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. PIPPI 2021 accepted 14 papers from the 18 submissions received. The workshop aims to bring together methods and experience from researchers and authors working on these younger cohorts and provides a forum for the open discussion of advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period.