Case-Based Reasoning on Images and Signals

by Petra Perner (Editor)

Overview

This book is the first edited book that deals with the special topic of signals and images within case-based reasoning (CBR). Signal-interpreting systems are becoming increasingly popular in medical, industrial, ecological, biotechnological and many other applications. Existing statisticalandknowledge-basedtechniqueslackrobustness,accuracy,and?- ibility. New strategies are needed that can adapt to changing environmental conditions, signal variation, user needs and process requirements. Introducing CBRstrategiesintosignal-interpretingsystemscansatisfytheserequirements. CBR can be used to control the signal-processing process in all phases of a signal-interpreting system to derive information of the highest possible quality. Beyond this CBR offers different learning capabilities, for all phases of a signal-interpretingsystem,thatsatisfydifferentneedsduringthedevelopment process of a signal-interpreting system. In the outline of this book we summarize under the term “signal” signals of 1-dimensional, 2-dimensional or 3-dimensional nature. The unique data and the necessary computation techniques require ext- ordinary case representations, similarity measures and CBR strategies to be utilised. Signalinterpretation(1D,2D,or3Dsignalinterpretation)istheprocessof mapping the numerical representation of a signal into logical representations suitable for signal descriptions. A signal-interpreting system must be able to extract symbolic features from the raw data e.g., the image (e.g., irregular structure inside the nodule, area of calcification, and sharp margin). This is a complex process; the signal passes through several general processing steps before the final symbolic description is obtained. The structure of the book is divided into a theoretical part and intoan application-oriented part.

Product Details

ISBN-13:	9783642092213
Publisher:	Springer Berlin Heidelberg
Publication date:	12/08/2010
Series:	Studies in Computational Intelligence , #73
Edition description:	Softcover reprint of hardcover 1st ed. 2008
Pages:	436
Product dimensions:	6.10(w) x 9.25(h) x 0.04(d)

Table of Contents

to Case-Based Reasoning for Signals and Images.- Similarity.- Distance Function Learning for Supervised Similarity Assessment.- Induction of Similarity Measures for Case Based Reasoning Through Separable Data Transformations.- Graph Matching.- Memory Structures and Organization in Case-Based Reasoning.- Learning a Statistical Model for Performance Prediction in Case-Based Reasoning.- A CBR Agent for Monitoring the Carbon Dioxide Exchange Rate from Satellite Images.- Extracting Knowledge from Sensor Signals for Case-Based Reasoning with Longitudinal Time Series Data.- Prototypes and Case-Based Reasoning for Medical Applications.- Case-Based Reasoning for Image Segmentation by Watershed Transformation.- Similarity-Based Retrieval for Biomedical Applications.- Medical Imagery in Case-Based Reasoning.- Instance-Based Relevance Feedback in Image Retrieval Using Dissimilarity Spaces.