Improving the ranking quality of medical image retrieval using a genetic feature selection method

Authors:
SéRgio Francisco Da Silva;Marcela Xavier Ribeiro;JoãO Do E. S. Batista Neto;Caetano Traina-Jr.;Agma J. M. Traina
Affiliations:
Department of Computer Science, University of Sao Paulo at Sao Carlos, Brazil;Department of Computer Science, Federal University of Sao Carlos, Brazil;Department of Computer Science, University of Sao Paulo at Sao Carlos, Brazil;Department of Computer Science, University of Sao Paulo at Sao Carlos, Brazil;Department of Computer Science, University of Sao Paulo at Sao Carlos, Brazil
Venue:
Decision Support Systems
Year:
2011

Citing 28
Cited 3

Optimizing similarity using multi-query relevance feedback

Journal of the American Society for Information Science
Applying genetic algorithms to query optimization in document retrieval

Information Processing and Management: an International Journal
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Modern Information Retrieval

Modern Information Retrieval
Discretization: An Enabling Technique

Data Mining and Knowledge Discovery
On the 'Dimensionality Curse' and the 'Self-Similarity Blessing'

IEEE Transactions on Knowledge and Data Engineering
Unsupervised Feature Selection Applied to Content-Based Retrieval of Lung Images

IEEE Transactions on Pattern Analysis and Machine Intelligence
When Is ''Nearest Neighbor'' Meaningful?

ICDT '99 Proceedings of the 7th International Conference on Database Theory
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning

ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Multiple query evaluation based on an enhanced genetic algorithm

Information Processing and Management: an International Journal - Modelling vagueness and subjectivity in information access
Order-based fitness functions for genetic algorithms applied to relevance feedback

Journal of the American Society for Information Science and Technology
Theoretical and Empirical Analysis of ReliefF and RReliefF

Machine Learning
Efficient Feature Selection via Analysis of Relevance and Redundancy

The Journal of Machine Learning Research
Toward Integrating Feature Selection Algorithms for Classification and Clustering

IEEE Transactions on Knowledge and Data Engineering
The effects of fitness functions on genetic programming-based ranking discovery for Web search: Research Articles

Journal of the American Society for Information Science and Technology
Feature Selection Based on Mutual Information: Criteria of Max-Dependency, Max-Relevance, and Min-Redundancy

IEEE Transactions on Pattern Analysis and Machine Intelligence
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)

Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Towards applying content-based image retrieval in the clinical routine

Future Generation Computer Systems
Selecting critical clinical features for heart diseases diagnosis with a real-coded genetic algorithm

Applied Soft Computing
Feature Selection Based on Genetic Algorithm for CBIR

CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 2 - Volume 02
A genetic programming framework for content-based image retrieval

Pattern Recognition
Feature selection based-on genetic algorithm for image annotation

Knowledge-Based Systems
Dimensionality reduction for knowledge discovery in medical claims database: Application to antidepressant medication utilization study

Computer Methods and Programs in Biomedicine
A feature selection technique for generation of classification committees and its application to categorization of laryngeal images

Pattern Recognition
Evolutionary-based feature selection approaches with new criteria for data mining: A case study of credit approval data

Expert Systems with Applications: An International Journal
Genetic-based approaches in ranking function discovery and optimization in information retrieval - A framework

Decision Support Systems
Using an image-extended relational database to support content-based image retrieval in a PACS

Computer Methods and Programs in Biomedicine
Search strategies for ensemble feature selection in medical diagnostics

CBMS'03 Proceedings of the 16th IEEE conference on Computer-based medical systems

Image retrieval employing genetic dissimilarity weighting and feature space transformation functions

Proceedings of the 27th Annual ACM Symposium on Applied Computing
Feature space optimization for content-based image retrieval

ACM SIGAPP Applied Computing Review
Robust feature selection based on regularized brownboost loss

Knowledge-Based Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we take advantage of single-valued functions that evaluate rankings to develop a family of feature selection methods based on the genetic algorithm approach, tailored to improve the accuracy of content-based image retrieval systems. Experiments on three image datasets, comprising images of breast and lung nodules, showed that developing functions to evaluate the ranking quality allows improving retrieval performance. This approach produces significantly better results than those of other fitness function approaches, such as the traditional wrapper and than filter feature selection algorithms.