Buch, Englisch, Band 11044, 101 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 195 g
Reihe: Image Processing, Computer Vision, Pattern Recognition, and Graphics
Second International Workshop, GRAIL 2018 and First International Workshop, Beyond MIC 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings
Buch, Englisch, Band 11044, 101 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 195 g
Reihe: Image Processing, Computer Vision, Pattern Recognition, and Graphics
ISBN: 978-3-030-00688-4
Verlag: Springer International Publishing
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
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
Weitere Infos & Material
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.