Machine Learning Meets Medical Imaging
First International Workshop, MLMMI 2015, Held in Conjunction with ICML 2015, Lille, France, July 11, 2015, Revised Selected Papers
Published on 29. December 2015
X, 105 pages
978-3-319-27929-9 (ISBN)
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This book constitutes the revised selected papers of the
First International Workshop on Machine Learning in Medical Imaging, MLMMI
2015, held in July 2015 in Lille, France, in conjunction with the 32nd
International Conference on Machine Learning, ICML 2015.
The 10 papers presented in this volume were carefully
reviewed and selected for inclusion in the book. The papers communicate the
specific needs and nuances of medical imaging to the machine learning community
while exposing the medical imaging community to current trends in machine
learning.
More details
Series
Edition
1st ed. 2015
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Product notice
Reflowable
Illustrations
X, 105 p. 31 illus. in color.
File size
8,23 MB
ISBN-13
978-3-319-27929-9 (9783319279299)
DOI
10.1007/978-3-319-27929-9
Schweitzer Classification
Other editions
Additional editions
Kanwal Bhatia | Herve Lombaert
Machine Learning Meets Medical Imaging
First International Workshop, MLMMI 2015, Held in Conjunction with ICML 2015, Lille, France, July 11, 2015, Revised Selected Papers
Book
12/2015
Springer
€42.80
Shipment within 10-15 days
Content
Retrospective motion correction of magnitude-input MR images.- Automatic Brain Localization in Fetal MRI Using Superpixel Graphs.- Learning Deep Temporal Representations for fMRI Brain Decoding.- Modelling Non-Stationary and Non-Separable Spatio-Temporal Changes in Neurodegeneration via Gaussian Process Convolution.- Improving MRI brain image classification with anatomical regional kernels.- A Graph Based Classification Method for Multiple Sclerosis Clinical Form Using Support Vector Machine.- Classification of Alzheimer's Disease using Discriminant Manifolds of Hippocampus Shapes.- Transfer Learning for Prostate Cancer Mapping Based on Multicentric MR imaging databases.
