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Signal and Image Analysis for Biomedical and Life Sciences

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Cover of 'Signal and Image Analysis for Biomedical and Life Sciences'

Table of Contents

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    Book Overview
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    Chapter 1 Visual Analytics of Signalling Pathways Using Time Profiles
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    Chapter 2 Modeling of testosterone regulation by pulse-modulated feedback.
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    Chapter 3 Hybrid Algorithms for Multiple Change-Point Detection in Biological Sequences
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    Chapter 4 Stochastic anomaly detection in eye-tracking data for quantification of motor symptoms in Parkinson's disease.
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    Chapter 5 Identification of the Reichardt Elementary Motion Detector Model
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    Chapter 6 Multi-complexity Ensemble Measures for Gait Time Series Analysis: Application to Diagnostics, Monitoring and Biometrics.
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    Chapter 7 Development of a motion capturing and load analyzing system for caregivers aiding a patient to sit up in bed.
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    Chapter 8 Classifying Epileptic EEG Signals with Delay Permutation Entropy and Multi-scale K-Means.
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    Chapter 9 Tracking of EEG Activity Using Motion Estimation to Understand Brain Wiring.
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    Chapter 10 Towards Automated Quantitative Vasculature Understanding via Ultra High-Resolution Imagery.
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    Chapter 11 Cloud based toolbox for image analysis, processing and reconstruction tasks.
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    Chapter 12 Pollen image classification using the classifynder system: algorithm comparison and a case study on new zealand honey.
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    Chapter 13 Digital image processing and analysis for activated sludge wastewater treatment.
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    Chapter 14 A Complete System for 3D Reconstruction of Roots for Phenotypic Analysis
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Title
Signal and Image Analysis for Biomedical and Life Sciences
Published by
Springer International Publishing, January 2015
DOI 10.1007/978-3-319-10984-8
ISBNs
978-3-31-910983-1, 978-3-31-910984-8
Authors

Sun, Changming

Editors

Changming Sun, Tomasz Bednarz, Tuan D. Pham, Pascal Vallotton, Dadong Wang

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