Digital Image Processing
Texture Classification by Wavelet Packet Signatures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Is early detection of liver and breast cancers from ultrasound scans possible?
Pattern Recognition Letters - Speciqal issue: Ultrasonic image processing and analysis
An Expert Support System for Breast Cancer Diagnosis using Color Wavelet Features
Journal of Medical Systems
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In this paper, a wavelet based approach is proposed for the detection and diagnosis of prostate cancer in Trans Rectal UltraSound (TRUS) images. A texture feature extraction filter was implemented to extract textural features from TRUS images that characterize malignant and benign tissues. The filter is based on the wavelet decomposition. It is demonstrated that the wavelet decomposition reveals details in the malignant and benign regions in TRUS images of the prostate which correlate with their pathological representations. The wavelet decomposition is applied to enhance the visual distinction between the malignant and benign regions, which could be used by radiologists as a supplementary tool for making manual classification decisions. The proposed filter could be used to extract texture features which linearly separate the malignant and benign regions in the feature domain. The extracted feature could be used as an input to a complex classifier for automated malignancy region classification.