Machine Learning Meets Medical Imaging
First International Workshop, MLMMI 2015, Held in Conjunction with ICML 2015, Lille, France, July 11, 2015, Revised Selected Papers
(Sprache: Englisch)
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Klappentext zu „Machine Learning Meets Medical Imaging “
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The 10 papers presented in this volume were carefullyreviewed and selected for inclusion in the book. The papers communicate thespecific needs and nuances of medical imaging to the machine learning communitywhile exposing the medical imaging community to current trends in machinelearning.
Inhaltsverzeichnis zu „Machine Learning Meets Medical Imaging “
Retrospectivemotion correction of magnitude-input MR images.- Automatic Brain Localizationin Fetal MRI Using Superpixel Graphs.- Learning Deep Temporal Representationsfor fMRI Brain Decoding.- Modelling Non-Stationary and Non-SeparableSpatio-Temporal Changes in Neurodegeneration via Gaussian Process Convolution.-Improving MRI brain image classification with anatomical regional kernels.- AGraph Based Classification Method for Multiple Sclerosis Clinical Form UsingSupport Vector Machine.- Classification of Alzheimer's Disease usingDiscriminant Manifolds of Hippocampus Shapes.- Transfer Learning for ProstateCancer Mapping Based on Multicentric MR imaging databases.
Bibliographische Angaben
- 2015, 1st ed. 2015, X, 105 Seiten, 105 farbige Abbildungen, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben: Kanwal K. Bhatia, Herve Lombaert
- Verlag: Springer, Berlin
- ISBN-10: 3319279289
- ISBN-13: 9783319279282
- Erscheinungsdatum: 30.12.2015
Sprache:
Englisch
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