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Metaheuristics for Medicine and Biology

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Cover of 'Metaheuristics for Medicine and Biology'

Table of Contents

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    Book Overview
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    Chapter 1 Design of Static Metaheuristics for Medical Image Analysis
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    Chapter 2 Multi-level Image Thresholding Based on Hybrid Differential Evolution Algorithm. Application on Medical Images
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    Chapter 3 Fuzzy Edge Detection in Computed Tomography Through Genetic Algorithm Optimization
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    Chapter 4 Particle Swarm Optimization Based Fast Chan-Vese Algorithm for Medical Image Segmentation
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    Chapter 5 Evidential Deformable Model for Contour Tracking. Application on Brain Cine MR Sequences
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    Chapter 6 Microscopic Image Segmentation Based on Based Branch and Bound and Game Theory
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    Chapter 7 Dynamic Metaheuristics for Brain Cine-MRI
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    Chapter 8 Lexicographic Approach Based on Evidence Theory for Blood Cell Image Segmentation
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    Chapter 9 Medical Image Denoising Using Metaheuristics
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    Chapter 10 Medical Image Registration Based on Metaheuristics: A Comparative Study
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    Chapter 11 Adaptive ECG Signal Filtering Using Bayesian Based Evolutionary Algorithm
Attention for Chapter 8: Lexicographic Approach Based on Evidence Theory for Blood Cell Image Segmentation
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Chapter title
Lexicographic Approach Based on Evidence Theory for Blood Cell Image Segmentation
Chapter number 8
Book title
Metaheuristics for Medicine and Biology
Published by
Springer, Berlin, Heidelberg, January 2017
DOI 10.1007/978-3-662-54428-0_8
Book ISBNs
978-3-66-254426-6, 978-3-66-254428-0
Authors

Ismahan Baghli, Amir Nakib

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