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Patch-Based Techniques in Medical Imaging: Second International Workshop, Patch-MI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings 1st ed. 2016 [Pehme köide]

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  • Formaat: Paperback / softback, 141 pages, kõrgus x laius: 235x155 mm, kaal: 2409 g, 45 Illustrations, black and white; X, 141 p. 45 illus., 1 Paperback / softback
  • Sari: Image Processing, Computer Vision, Pattern Recognition, and Graphics 9993
  • Ilmumisaeg: 22-Sep-2016
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319471171
  • ISBN-13: 9783319471174
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Patch-Based Techniques in Medical Imaging: Second International Workshop, Patch-MI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Proceedings 1st ed. 2016Suurem pilt
  • Formaat: Paperback / softback, 141 pages, kõrgus x laius: 235x155 mm, kaal: 2409 g, 45 Illustrations, black and white; X, 141 p. 45 illus., 1 Paperback / softback
  • Sari: Image Processing, Computer Vision, Pattern Recognition, and Graphics 9993
  • Ilmumisaeg: 22-Sep-2016
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319471171
  • ISBN-13: 9783319471174
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783319471174.html
Märksõnad:
This book constitutes the refereed proceedings of the Second International Workshop on Patch-Based Techniques in Medical Images, Patch-MI 2016, which was held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016.





The 17 regular papers presented in this volume were carefully reviewed and selected from 25 submissions.





The main aim of the Patch-MI 2016 workshop is to promote methodological advances within the medical imaging field, with various applications in image segmentation, image denoising, image super-resolution, computer-aided diagnosis, image registration, abnormality detection, and image synthesis.
Automatic Segmentation of Hippocampus for Longitudinal Infant Brain MR
Image Sequence by Spatial-Temporal Hypergraph Learning.- Construction of
Neonatal Diffusion Atlases via Spatio-Angular Consistency.- Selective
Labeling: identifying representative sub-volumes for interactive
segmentation.- Robust and Accurate Appearance Models based on Joint
Dictionary Learning: Data from the Osteoarthritis Initiative.- Consistent
multi-atlas hippocampus segmentation for longitudinal MR brain images with
temporal sparse representation.- Sparse-Based Morphometry: Principle and
Application to Alzheimers Disease.- Multi-Atlas Based Segmentation of
Brainstem Nuclei from MR Images by Deep Hyper-Graph Learning.- Patch-Based
Discrete Registration of Clinical Brain Images.- Non-local MRI Library-based
Super-resolution: Application to Hippocampus Subfield Segmentation.-
Patch-based DTI grading: Application to Alzheimer's disease classification.-
Hierarchical Multi-Atlas Segmentation using Label-SpecificEmbeddings,
Target-Specific Templates and Patch Refinement.- HIST: HyperIntensity
Segmentation Tool.- Supervoxel-Based Hierarchical Markov Random Field
Framework for Multi-Atlas Segmentation.- CapAIBL: Automated reporting of
cortical PET quantification without need of MRI on brain surface using a
patch-based method.- High resolution hippocampus subfield segmentation using
multispectral multi-atlas patch-based label fusion.- Identification of water
and fat images in Dixon MRI using aggregated patch-based convolutional neural
networks.- Estimating Lung Respiratory Motion Using Combined Global and Local
Statistical Models.