Graphs in Biomedical Image Analysis and Integrating Medical Imaging and Non-Imaging Modalities: Second International Workshop, GRAIL 2018 and First International Workshop, Beyond MIC 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings: Lecture Notes in Computer Science, cartea 11044
Editat de Danail Stoyanov, Zeike Taylor, Enzo Ferrante, Adrian V. Dalca, Anne Martel, Lena Maier-Hein, Sarah Parisot, Aristeidis Sotiras, Bartlomiej Papiez, Mert R. Sabuncu, Li Shenen Limba Engleză Paperback – 16 sep 2018
The 6 full papers presented at GRAIL 2018 and the 5 full papers presented at BeYond MIC 2018 were carefully reviewed and selected. The GRAIL papers cover a wide range of develop graph-based models for the analysis of biomedical images and encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts. The Beyond MIC papers cover topics of novel methods with significant imaging and non-imaging components, addressing practical applications and new datasets
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Specificații
ISBN-13: 9783030006884
ISBN-10: 3030006883
Pagini: 106
Ilustrații: XVI, 101 p. 26 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.18 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Image Processing, Computer Vision, Pattern Recognition, and Graphics
Locul publicării:Cham, Switzerland
ISBN-10: 3030006883
Pagini: 106
Ilustrații: XVI, 101 p. 26 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.18 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Image Processing, Computer Vision, Pattern Recognition, and Graphics
Locul publicării:Cham, Switzerland
Cuprins
Graph Saliency Maps through Spectral Convolutional Networks: Application to Sex Classification with Brain Connectivity.- A Graph Representation and Similarity Measure for Brain Networks with Nodal Features.- Hierarchical Bayesian Networks for Modeling Inter-Class Dependencies: Application to Semi-Supervised Cell Segmentation.- Multi-modal Disease Classification in Incomplete Datasets Using Geometric Matrix Completion.- BrainParcel: A Brain Parcellation Algorithm for Cognitive State Classification.- Modeling Brain Networks with Artificial Neural Networks.- A Bayesian Disease Progression Model for Clinical Trajectories.- Multi-modal brain connectivity study using deep collaborative learning.- Towards Subject and Diagnostic Identifiability in the Alzheimer’s Disease Spectrum based on Functional Connectomes.- Predicting Conversion of Mild Cognitive Impairments to Alzheimer’s Disease and Exploring Impact of Neuroimaging.- Cross-Diagnostic Prediction of Dimensional Psychiatric Phenotypes inAnorexia Nervosa and Body Dysmorphic Disorder Using Multimodal Neuroimaging and Psychometric Data.