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Characterization of visually similar diffuse diseases from B-scan liver images using nonseparable wavelet transform
- Source :
- IEEE Transactions on Medical Imaging. 17:541-549
- Publication Year :
- 1998
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 1998.
-
Abstract
- This paper describes a new approach for texture characterization, based on nonseparable wavelet decomposition, and its application for the discrimination of visually similar diffuse diseases of liver. The proposed feature-extraction algorithm applies nonseparable quincunx wavelet transform and uses energies of the transformed regions to characterize textures. Classification experiments on a set of three different tissue types show that the scale/frequency approach, particularly one based on the nonseparable wavelet transform, could be a reliable method for a texture characterization and analysis of B-scan liver images. Comparison between the quincunx and the traditional wavelet decomposition suggests that the quincunx transform is more appropriate for characterization of noisy data, and practical applications, requiring description with lower rotational sensitivity.
- Subjects :
- Liver Cirrhosis
Discrete wavelet transform
Rotation
Computer science
Stationary wavelet transform
Feature extraction
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Wavelet packet decomposition
Diagnosis, Differential
Wavelet
Image texture
Humans
Computer vision
Electrical and Electronic Engineering
Continuous wavelet transform
Ultrasonography
Radiological and Ultrasound Technology
business.industry
Liver Diseases
Second-generation wavelet transform
Wavelet transform
Computer Science Applications
Fatty Liver
Artificial intelligence
business
Harmonic wavelet transform
Algorithms
Software
Subjects
Details
- ISSN :
- 02780062
- Volume :
- 17
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Medical Imaging
- Accession number :
- edsair.doi.dedup.....0f0f409d7236c3448779c7602fe56de1