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024 7 _a10.1007/978-3-030-50120-4
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082 0 4 _a006.37
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245 1 0 _aBiomedical Image Registration
_h[electronic resource] :
_b9th International Workshop, WBIR 2020, Portorož, Slovenia, December 1-2, 2020, Proceedings /
_cedited by Žiga Špiclin, Jamie McClelland, Jan Kybic, Orcun Goksel.
250 _a1st ed. 2020.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2020.
300 _aX, 176 p. 70 illus., 44 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
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_2rdacarrier
347 _atext file
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490 1 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v12120
505 0 _aRegistration Initialization and Acceleration -- Nonlinear Alignment of Whole Tractograms with the Linear Assignment Problem -- Learning-based Affine Registration of Histological Images -- Enabling Manual Intervention for Otherwise Automated Registration of Large Image Series -- Towards Segmentation and Spatial Alignment of the Human Embryonic Brain using Deep Learning for Atlas-based Registration -- Learning Deformable Image Registration with Structure Guidance Constraints for Adaptive Radiotherapy -- Interventional Registration -- Multilevel 2D-3D Intensity-based Image Registration -- Towards Automated Spine Mobility Quantification: a Locally Rigid CT to X-ray Registration Framework -- Landmark based Registration -- Reinforced Redetection of Landmark in Pre- and Post-Operative Brain Scan using Anatomical Guidance for Image Alignment -- Deep Volumetric Feature Encoding for Biomedical Images -- Multi-Channel Registration -- Multi-Channel Image Registration of Cardiac MR Using Supervised Feature Learning with Convolutional Encoder-Decoder Network -- Multi-Channel Registration for Diffusion MRI: Longitudinal Analysis for the Neonatal Brain -- An Image Registration-based Method for EPI Distortion Correction based on Opposite Phase Encoding (COPE) -- Diffusion Tensor driven Image registration: a Deep Learning Approach -- Multimodal MRI Template Creation in the Ring-Tailed Lemur and Rhesus Macaque -- Sliding Motion -- An Unsupervised Learning Approach to Discontinuity-preserving Image Registration -- An Image Registration Framework for Discontinuous Mappings along Cracks.
520 _aThis book constitutes the refereed proceedings of the 9th International Workshop on Biomedical Image Registration, WBIR 2020, which was supposed to be held in Portorož, Slovenia, in June 2020. The conference was postponed until December 2020 due to the COVID-19 pandemic. The 16 full and poster papers included in this volume were carefully reviewed and selected from 22 submitted papers. The papers are organized in the following topical sections: Registration initialization and acceleration, interventional registration, landmark based registration, multi-channel registration, and sliding motion.
650 0 _aComputer vision.
_9111081
650 0 _aArtificial intelligence.
_93407
650 0 _aPattern recognition systems.
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650 0 _aApplication software.
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650 0 _aComputer engineering.
_910164
650 0 _aComputer networks .
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650 0 _aComputers.
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650 1 4 _aComputer Vision.
_9111083
650 2 4 _aArtificial Intelligence.
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650 2 4 _aAutomated Pattern Recognition.
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650 2 4 _aComputer and Information Systems Applications.
_9111084
650 2 4 _aComputer Engineering and Networks.
_9111085
650 2 4 _aComputing Milieux.
_955441
700 1 _aŠpiclin, Žiga.
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700 1 _aMcClelland, Jamie.
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700 1 _aKybic, Jan.
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700 1 _aGoksel, Orcun.
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
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856 4 0 _uhttps://doi.org/10.1007/978-3-030-50120-4
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