Application of wavelet transforms and bayes classifier to segmentation of ultrasound images

Authors:
Paweł Kieś
Affiliations:
Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
Venue:
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Year:
2005

Citing 7
Cited 0

Algorithms for clustering data

Algorithms for clustering data
Multiresolution Feature Extraction and Selection for Texture Segmentation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Ten lectures on wavelets

Ten lectures on wavelets
The nature of statistical learning theory

The nature of statistical learning theory
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)
An Efficient and Effective Texture Classifaction Approach Using a New Notion in Wavelet Theory

ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
Texture classification and segmentation using wavelet frames

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

An approach for segmentation of ultrasound images using features extracted by orthogonal wavelet transforms that can be used in an interactive system is proposed. These features are the training data for the K-means clustering algorithm and the Bayes classifier. The result of classification is improved by using neighbourhood information.