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müller henning (curatore); wells iii william m. (curatore); zhang shaoting (curatore); chung albert c.s. (curatore); jenkinson mark (curatore); ribbens annemie (curatore); kelm b. michael (curatore); arbel tal (curatore); cai weidong (curatore) - medical computer vision and bayesian and graphical models for biomedical imaging

Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers

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Dettagli

Genere:Libro
Lingua: Inglese
Editore:

Springer

Pubblicazione: 07/2017
Edizione: 1st ed. 2017





Trama

This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision, MCV 2016, and of the International Workshop on Bayesian and grAphical Models for Biomedical Imaging, BAMBI 2016, held in Athens, Greece, in October 2016, held in conjunction with the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016.
The 13 papers presented in MCV workshop and the 6 papers presented in BAMBI workshop were carefully reviewed and selected from numerous submissions.
The goal of the MCV workshop is to explore the use of "big data” algorithms for harvesting, organizing and learning from large-scale medical imaging data sets and for general-purpose automatic understanding of medical images.
The BAMBI workshop aims to highlight the potential of using Bayesian or random field graphical models for advancing research in biomedical image analysis.





Sommario

Constructing Subject- and Disease-Specific Effect Maps: Application to Neurodegenerative Diseases.- BigBrain: Automated Cortical Parcellation and Comparison with Existing Brain Atlases.- LATEST: Local AdapTivE and Sequential Training for Tissue Segmentation of Isointense Infant Brain MR Images.- Landmark-based Alzheimer's Disease Diagnosis Using Longitudinal Structural MR Images.- Inferring Disease Status by non-Parametric Probabilistic Embedding.- A Lung Graph-Model for Pulmonary Hypertension and Pulmonary Embolism Detection on DECT Images.- Explaining Radiological Emphysema Subtypes with Unsupervised Texture Prototypes: MESA COPD Study.- Automatic Segmentation of Abdominal MRI Using Selective Sampling and Random Walker.- Gaze2Segment: A Pilot Study for Integrating Eye-Tracking Technology into Medical Image Segmentation.- Automatic Detection of Histological Artifacts in Mouse Brain Slice Images.- Lung Nodule Classification by Jointly Using Visual Descriptors and Deep Features.- Representation Learning for Cross-Modality Classification.- Guideline-based Machine Learning for Standard Plane Extraction in 3D Cardiac Ultrasound.- A Statistical Model for Simultaneous Template Estimation, Bias Correction, and Registration of 3D Brain Images.- Bayesian Multiview Manifold Learning Applied to Hippocampus Shape and Clinical Score Data.- Rigid Slice-To-Volume Medical Image Registration through Markov Random Fields.- Sparse Probabilistic Parallel Factor Analysis for the Modeling of PET and Task-fMRI data.- Non-local Graph-based Regularization for Deformable Image Registration.- Unsupervised Framework for Consistent Longitudinal MS Lesion Segmentation. 











Altre Informazioni

ISBN:

9783319611877

Condizione: Nuovo
Collana: Lecture Notes in Computer Science
Dimensioni: 235 x 155 mm Ø 3635 gr
Formato: Brossura
Illustration Notes:XIII, 222 p. 75 illus.
Pagine Arabe: 222
Pagine Romane: xiii


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