Machine Learning Meets Medical Imaging
Springer International Publishing (Verlag)
978-3-319-27928-2 (ISBN)
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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.
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.
| Erscheinungsdatum | 08.10.2016 |
|---|---|
| Reihe/Serie | Image Processing, Computer Vision, Pattern Recognition, and Graphics | Lecture Notes in Computer Science |
| Zusatzinfo | X, 105 p. 31 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Schlagworte | Alzheimer's disease • Applications • Bioinformatics • brain • classification • clinical classification • Computational Biology • computer-aided detection system • Computer Science • computer vision • conference proceedings • Gaussian processes • graph kernel • image processing and computer vision • Informatics • Interpretability • learning • machine learning • Mathematical Analysis • MRI • multi-kernel • Multiple Sclerosis • Research • structural connectome • SVM • transfer learning |
| ISBN-10 | 3-319-27928-9 / 3319279289 |
| ISBN-13 | 978-3-319-27928-2 / 9783319279282 |
| Zustand | Neuware |
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