Table of contents

A Generic Method for Evaluating Appearance Models and Assessing the Accuracy of NRR

Overview

Motivation

Existing Methods of Assessment

Model-Based Assessment

Model-based Framework

Building an Appearance Model

Training and Synthetic Images

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Model Quality

Measuring Inter-Image Distance

Shuffle Distance

Varying Shuffle Radius

Validation Experiments

Experimental Design

Brain Data

Perturbation Framework

Examples of Perturbed Images

Results – Generalised Overlap

Results – Model-Based

Results – Comparison

Results – Sensitivities

Further Tests – Noise

Practical Application

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Practical Application - Results

Extension to 3-D

Conclusions

Author: Roy Schestowitz

E-mail: r at schestowitz dot com

Homepage: http://schestowitz.com/

Further information:
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