Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
C4.5: programs for machine learning
C4.5: programs for machine learning
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Learning from Data: Concepts, Theory, and Methods
Learning from Data: Concepts, Theory, and Methods
Aggressive region growing for speckle reduction in ultrasound images
Pattern Recognition Letters - Speciqal issue: Ultrasonic image processing and analysis
Pattern Recognition Letters - Speciqal issue: Ultrasonic image processing and analysis
Pattern Recognition Letters - Speciqal issue: Ultrasonic image processing and analysis
Ultrasound speckle reduction by directional median filtering
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 1)-Volume 1 - Volume 1
A diffusion stick method for speckle suppression in ultrasonic images
Pattern Recognition Letters
Approaches for automated detection and classification of masses in mammograms
Pattern Recognition
A versatile technique for visual enhancement of medical ultrasound images
Digital Signal Processing
Diagnosis of breast tumors with ultrasonic texture analysis using support vector machines
Neural Computing and Applications
A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Enhancement and Noise Filtering by Use of Local Statistics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Noise Smoothing Filter for Images with Signal-Dependent Noise
IEEE Transactions on Pattern Analysis and Machine Intelligence
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Spatially adaptive wavelet thresholding with context modeling for image denoising
IEEE Transactions on Image Processing
Speckle reducing anisotropic diffusion
IEEE Transactions on Image Processing
Adaptive color segmentation-a comparison of neural and statistical methods
IEEE Transactions on Neural Networks
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Automatic region of interest generation for kidney ultrasound images
ACS'11 Proceedings of the 11th WSEAS international conference on Applied computer science
A comparative study of ultrasound image segmentation algorithms for segmenting kidney tumors
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
Ultrasonic liver tissue characterization by feature fusion
Expert Systems with Applications: An International Journal
Support vector machine for breast MR image classification
Computers & Mathematics with Applications
InstanceRank based on borders for instance selection
Pattern Recognition
A Robust Method for Ventriculomegaly Detection from Neonatal Brain Ultrasound Images
Journal of Medical Systems
Computer Aided Diagnosis System for Breast Cancer Based on Color Doppler Flow Imaging
Journal of Medical Systems
MCV'12 Proceedings of the Second international conference on Medical Computer Vision: recognition techniques and applications in medical imaging
Journal of Visual Communication and Image Representation
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Breast cancer is the second leading cause of death for women all over the world. Since the cause of the disease remains unknown, early detection and diagnosis is the key for breast cancer control, and it can increase the success of treatment, save lives and reduce cost. Ultrasound imaging is one of the most frequently used diagnosis tools to detect and classify abnormalities of the breast. In order to eliminate the operator dependency and improve the diagnostic accuracy, computer-aided diagnosis (CAD) system is a valuable and beneficial means for breast cancer detection and classification. Generally, a CAD system consists of four stages: preprocessing, segmentation, feature extraction and selection, and classification. In this paper, the approaches used in these stages are summarized and their advantages and disadvantages are discussed. The performance evaluation of CAD system is investigated as well.