Fundamentals of digital image processing
Fundamentals of digital image processing
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detecting texture periodicity from the co-occurrence matrix
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image characterizations based on joint gray level-run length distributions
Pattern Recognition Letters
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
Features and classification methods to locate deciduous trees in images
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5 - Volume 5
A study of cloud classification with neural networks using spectral and textural features
IEEE Transactions on Neural Networks
Classification of heart sounds using an artificial neural network
Pattern Recognition Letters
Unsupervised segmentation of medical images using DCT coefficients
VIP '05 Proceedings of the Pan-Sydney area workshop on Visual information processing
An incremental neural network for tissue segmentation in ultrasound images
Computer Methods and Programs in Biomedicine
Tissue segmentation in ultrasound images by using genetic algorithms
Expert Systems with Applications: An International Journal
Heart Cavity Segmentation in Ultrasound Images Based on Supervised Neural Networks
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
A novel approach for distributed application scheduling based on prediction of communication events
Future Generation Computer Systems
Image segmentation using fuzzy logic, neural networks and genetic algorithms: survey and trends
Machine Graphics & Vision International Journal
International Journal of High Performance Systems Architecture
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A hybrid neural network is presented for the segmentation of ultrasound images.Feature vectors are formed by the discrete cosine transform of pixel intensities in region of interest (ROI). The elements and the dimension of the feature vectors are determined by considering only two parameters: The amount of ignored coefficients, and the dimension of the ROI.First-layer-nodes of the proposed hybrid network represent hyperspheres (HSs) in the feature space. Feature space is partitioned by intersecting these HSs to represent the distribution of classes. The locations and radii of the HSs are found by the genetic algorithms.Restricted Coulomb energy (RCE) network, modified RCE network, multi-layer perceptron and the proposed hybrid neural network are examined comparatively for the segmentation of ultrasound images.