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Biomedical Image Registration

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Cover of 'Biomedical Image Registration'

Table of Contents

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    Book Overview
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    Chapter 1 Nonlinear Alignment of Whole Tractograms with the Linear Assignment Problem
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    Chapter 2 Learning-Based Affine Registration of Histological Images
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    Chapter 3 Enabling Manual Intervention for Otherwise Automated Registration of Large Image Series
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    Chapter 4 Towards Segmentation and Spatial Alignment of the Human Embryonic Brain Using Deep Learning for Atlas-Based Registration
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    Chapter 5 Learning Deformable Image Registration with Structure Guidance Constraints for Adaptive Radiotherapy
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    Chapter 6 Multilevel 2D-3D Intensity-Based Image Registration
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    Chapter 7 Towards Automated Spine Mobility Quantification: A Locally Rigid CT to X-ray Registration Framework
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    Chapter 8 Reinforced Redetection of Landmark in Pre- and Post-operative Brain Scan Using Anatomical Guidance for Image Alignment
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    Chapter 9 Deep Volumetric Feature Encoding for Biomedical Images
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    Chapter 10 Multi-channel Image Registration of Cardiac MR Using Supervised Feature Learning with Convolutional Encoder-Decoder Network
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    Chapter 11 Multi-channel Registration for Diffusion MRI: Longitudinal Analysis for the Neonatal Brain
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    Chapter 12 An Image Registration-Based Method for EPI Distortion Correction Based on Opposite Phase Encoding (COPE)
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    Chapter 13 Diffusion Tensor Driven Image Registration: A Deep Learning Approach
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    Chapter 14 Multimodal MRI Template Creation in the Ring-Tailed Lemur and Rhesus Macaque
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    Chapter 15 An Unsupervised Learning Approach to Discontinuity-Preserving Image Registration
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    Chapter 16 An Image Registration Framework for Discontinuous Mappings Along Cracks
Attention for Chapter 5: Learning Deformable Image Registration with Structure Guidance Constraints for Adaptive Radiotherapy
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Chapter title
Learning Deformable Image Registration with Structure Guidance Constraints for Adaptive Radiotherapy
Chapter number 5
Book title
Biomedical Image Registration
Published by
Springer, Cham, December 2020
DOI 10.1007/978-3-030-50120-4_5
Book ISBNs
978-3-03-050119-8, 978-3-03-050120-4
Authors

Sven Kuckertz, Nils Papenberg, Jonas Honegger, Tomasz Morgas, Benjamin Haas, Stefan Heldmann, Kuckertz, Sven, Papenberg, Nils, Honegger, Jonas, Morgas, Tomasz, Haas, Benjamin, Heldmann, Stefan

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X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 23%
Researcher 3 23%
Student > Master 3 23%
Student > Bachelor 1 8%
Unspecified 1 8%
Other 1 8%
Unknown 1 8%
Readers by discipline Count As %
Computer Science 3 23%
Engineering 2 15%
Medicine and Dentistry 2 15%
Nursing and Health Professions 1 8%
Unspecified 1 8%
Other 2 15%
Unknown 2 15%