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Machine Learning Meets Medical Imaging [electronic resource] : First International Workshop, MLMMI 2015, Held in Conjunction with ICML 2015, Lille, France, July 11, 2015, Revised Selected Papers / edited by Kanwal K. Bhatia, Herve Lombaert.

Contributor(s): Material type: TextTextLanguage: English Series: Lecture Notes in Computer Science ; 9487Publication details: Cham : Springer International Publishing, 2015.Edition: 1st ed. 2015Description: 1 online resource (X, 105 p. 31 ill. in color.)ISBN:
  • 9783319279299
Subject(s): Online resources:
Contents:
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.
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Item type Current library Call number Materials specified Status Date due Barcode Item holds
Books Books National Library of India Available EBK000025324ENG
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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.

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