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Topics in Medical Image Processing and Computational Vision

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Cover of 'Topics in Medical Image Processing and Computational Vision'

Table of Contents

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    Book Overview
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    Chapter 1 Learning a Family of Detectors via Multiplicative Kernels
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    Chapter 2 Facial Expression Recognition Using FAPs-Based 3DMMM
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    Chapter 3 SVM Framework for Incorporating Content-Based Image Retrieval and Data Mining into the SBIM Image Manager
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    Chapter 4 Identification of Foliar Diseases in Cotton Crop
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    Chapter 5 Towards Ontological Cognitive System
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    Chapter 6 A Novel Edge Detector Based on Discrete t-norms for Noisy Images
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    Chapter 7 Colour Quantisation as a Preprocessing Step for Image Segmentation
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    Chapter 8 Medical Imaging and Computational Flow Models in Deformable Ducts
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    Chapter 9 Tracking Red Blood Cells in Microchannels: A Comparative Study Between an Automatic and a Manual Method
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    Chapter 10 A Survey for the Automatic Classification of Bone Tissue Images
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    Chapter 11 Colour Video Segmentation for the Quantification of Sweat Dynamic Function
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    Chapter 12 Current Issues in Medical Thermography
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    Chapter 13 Detection of Anatomic Structures in Retinal Images
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    Chapter 14 Database System for Clinical and Computer Assisted Diagnosis of Dermoscopy Images
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    Chapter 15 Segmentation Based Pattern Recognition for Peri-Urban Areas in X Band SAR Images
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    Chapter 16 Improving Flood Risk Management in the City of Lisbon: Developing a Detailed and Updated Map of Imperviousness Using Satellite Imagery
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Title
Topics in Medical Image Processing and Computational Vision
Published by
Springer Netherlands, January 2013
DOI 10.1007/978-94-007-0726-9
ISBNs
978-9-40-070725-2, 978-9-40-070726-9
Editors

João Manuel R.S. Tavares, Renato M. Natal Jorge

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Iran, Islamic Republic of 1 3%
United States 1 3%
Portugal 1 3%
Poland 1 3%
Unknown 25 86%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 21%
Student > Ph. D. Student 6 21%
Other 4 14%
Student > Doctoral Student 3 10%
Student > Bachelor 3 10%
Other 7 24%
Readers by discipline Count As %
Engineering 11 38%
Computer Science 4 14%
Medicine and Dentistry 3 10%
Neuroscience 2 7%
Arts and Humanities 1 3%
Other 7 24%
Unknown 1 3%