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

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 /

Mentés helye:
Bibliográfiai részletek
Testületi szerző:
SpringerLink (Online service), közreadó testület
Közreműködő(k):
Müller, Henning, szerk.
Különgyűjtemény:e-book
Formátum: könyv
Nyelv:angol
Megjelenés: Cham : Springer International Publishing, 2017
Sorozat:Image Processing, Computer Vision, Pattern Recognition, and Graphics
Tárgyszavak:
egészségügyi adatok > adatfeldolgozás
számítógépes látás > informatika > konferencia
Computer vision.
Medical records > Data processing.
Artificial intelligence.
Computer science.
Optical pattern recognition.
Image Processing and Computer Vision.
Health Informatics.
Artificial Intelligence (incl. Robotics).
Probability and Statistics in Computer Science.
Math Applications in Computer Science.
Pattern Recognition.
elektronikus könyv
konferenciakötet
tanulmányok
Online elérés:https://doi.org/10.1007/978-3-319-61188-4
Címkék: Új címke
A tételhez itt fűzhet saját címkét!
id opac-EUL01-000954011
collection e-book
institution L_042
EUL01
spelling 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 / edited by Henning Müller [et al.]
Cham Springer International Publishing 2017
XIII, 222 p. ill.
szöveg txt rdacontent
számítógépes c rdamedia
távoli hozzáférés cr rdacarrier
szövegfájl PDF rda
Image Processing, Computer Vision, Pattern Recognition, and Graphics
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. .
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.
Nyomtatott kiadás: ISBN 9783319611877
Nyomtatott kiadás: ISBN 9783319611891
Az e-könyvek a teljes ELTE IP-tartományon belül online elérhetők.
könyv
e-book
egészségügyi adatok adatfeldolgozás EUL10001009098 Y
számítógépes látás informatika konferencia EUL10001007248 Y
Computer vision. EUL10000467498 Y
Medical records Data processing. EUL10001087178 Y
Artificial intelligence. EUL10000183324 Y
Computer science. EUL10000449227 Y
Optical pattern recognition. EUL10001087156 Y
Image Processing and Computer Vision. http://scigraph.springernature.com/things/product-market-codes/I22021
Health Informatics. http://scigraph.springernature.com/things/product-market-codes/I23060
Artificial Intelligence (incl. Robotics). http://scigraph.springernature.com/things/product-market-codes/I21017
Probability and Statistics in Computer Science. http://scigraph.springernature.com/things/product-market-codes/I17036
Math Applications in Computer Science. http://scigraph.springernature.com/things/product-market-codes/I17044
Pattern Recognition. http://scigraph.springernature.com/things/product-market-codes/I2203X
elektronikus könyv
konferenciakötet
tanulmányok
Müller, Henning szerk. EUL10001017006 Y
SpringerLink (Online service) közreadó testület
Image Processing, Computer Vision, Pattern Recognition, and Graphics EUL10001014295 Y
Online változat https://doi.org/10.1007/978-3-319-61188-4
Cham Springer International Publishing Imprint: Springer 201
EUL01
language English
format Book
author2 Müller, Henning, szerk.
author_facet Müller, Henning, szerk.
SpringerLink (Online service), közreadó testület
author_corporate SpringerLink (Online service), közreadó testület
author_sort Müller, Henning
title 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
spellingShingle 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
Image Processing, Computer Vision, Pattern Recognition, and Graphics
egészségügyi adatok -- adatfeldolgozás
számítógépes látás -- informatika -- konferencia
Computer vision.
Medical records -- Data processing.
Artificial intelligence.
Computer science.
Optical pattern recognition.
Image Processing and Computer Vision.
Health Informatics.
Artificial Intelligence (incl. Robotics).
Probability and Statistics in Computer Science.
Math Applications in Computer Science.
Pattern Recognition.
elektronikus könyv
konferenciakötet
tanulmányok
title_sub MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers /
title_short Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging
title_full 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 / edited by Henning Müller [et al.]
title_fullStr 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 / edited by Henning Müller [et al.]
title_full_unstemmed 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 / edited by Henning Müller [et al.]
title_auth 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 /
title_sort 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
series Image Processing, Computer Vision, Pattern Recognition, and Graphics
series2 Image Processing, Computer Vision, Pattern Recognition, and Graphics
publishDate 2017
publishDateSort 2017
physical XIII, 222 p. : ill.
isbn 978-3-319-61188-4
callnumber-raw 14527
callnumber-search 14527
topic egészségügyi adatok -- adatfeldolgozás
számítógépes látás -- informatika -- konferencia
Computer vision.
Medical records -- Data processing.
Artificial intelligence.
Computer science.
Optical pattern recognition.
Image Processing and Computer Vision.
Health Informatics.
Artificial Intelligence (incl. Robotics).
Probability and Statistics in Computer Science.
Math Applications in Computer Science.
Pattern Recognition.
elektronikus könyv
konferenciakötet
tanulmányok
topic_facet egészségügyi adatok -- adatfeldolgozás
számítógépes látás -- informatika -- konferencia
Computer vision.
Medical records -- Data processing.
Artificial intelligence.
Computer science.
Optical pattern recognition.
Image Processing and Computer Vision.
Health Informatics.
Artificial Intelligence (incl. Robotics).
Probability and Statistics in Computer Science.
Math Applications in Computer Science.
Pattern Recognition.
elektronikus könyv
konferenciakötet
tanulmányok
egészségügyi adatok
számítógépes látás
Computer vision.
Medical records
Artificial intelligence.
Computer science.
Optical pattern recognition.
Image Processing and Computer Vision.
Health Informatics.
Artificial Intelligence (incl. Robotics).
Probability and Statistics in Computer Science.
Math Applications in Computer Science.
Pattern Recognition.
adatfeldolgozás
informatika
konferencia
Data processing.
url https://doi.org/10.1007/978-3-319-61188-4
illustrated Illustrated
first_indexed 2023-12-27T20:07:39Z
last_indexed 2023-12-30T20:55:01Z
recordtype opac
publisher Cham : Springer International Publishing
_version_ 1786737959356071936
score 13,3755665
generalnotes 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.

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