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Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology : Third International Workshop, MLCN 2020, and Second International Workshop, RNO-AI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings (Image Processing, Computer Vision, Pattern Recognition, and Graphics)

By: Ahmed Abdulkadir (Edited by) , Chantal Tax (Edited by) , Cher Bass (Edited by) , Hassan Mohy-ud-Din (Edited by) , Hongzhi Wang (Edited by) , Jane Maryam Rondina (Edited by) , Mohamad Habes (Edited by) , Saima Rathore (Edited by) , Seyed Mostafa Kia (Edited by) , Thomas Wolfers (Edited by)

Extended Catalogue

Ksh 10,250.00

Format: Paperback or Softback

ISBN-10: 3030668428

ISBN-13: 9783030668426

Collection / Series: Image Processing, Computer Vision, Pattern Recognition, and Graphics

Collection Type: Publisher collection

Edition statement: 1st ed. 2020

Publisher: Springer Nature Switzerland AG

Imprint: Springer Nature Switzerland AG

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Dec 31st, 2020

Publication Status: Active

Product extent: 305 Pages

Product Classification / Subject(s): Medical imaging
Machine learning
Image processing

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This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2020, and the Second International Workshop on Radiogenomics in Neuro-oncology, RNO-AI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020.*For MLCN 2020, 18 papers out of 28 submissions were accepted for publication. The accepted papers present novel contributions in both developing new machine learning methods and applications of existing methods to solve challenging problems in clinical neuroimaging. For RNO-AI 2020, all 8 submissions were accepted for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience. *The workshops were held virtually due to the COVID-19 pandemic.
This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2020, and the Second International Workshop on Radiogenomics in Neuro-oncology, RNO-AI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020.*

For MLCN 2020, 18 papers out of 28 submissions were accepted for publication. The accepted papers present novel contributions in both developing new machine learning methods and applications of existing methods to solve challenging problems in clinical neuroimaging.

For RNO-AI 2020, all 8 submissions were accepted for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience.

*The workshops were held virtually due to the COVID-19 pandemic.


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