Learn More
In this paper, a fully automated method for segmenting Left Ventricle (LV) in echocardiography images is proposed. A new method named active ellipse model is developed to automatically find the best ellipse inside the LV chamber without intervention of any specialist. A modified B-Spline Snake algorithm is used to segment the LV chamber in which the initial(More)
This paper presents a study investigating the potential of artiicial neural networks (ANN's) for the classiication and segmentation of magnetic resonance (MR) images of the human brain. In this study, we present the application of a Learning Vector Quantization (LVQ) Artiicial Neural Network (ANN) for the multispectral supervised classiication of MR images.(More)
Dictionary learning for sparse representation has recently attracted attention among the signal processing society in a variety of applications such as denoising, classification, and compression. The number of elements in a learned dictionary is crucial since it governs specificity and optimality of sparse representation. Sparsity level, number of(More)
The preprocessing step of most computer-aided diagnosis (CAD) systems for identifying the lung diseases is lung segmentation. We present a novel lung segmentation technique based on watershed transform, which is fast and accurate. Lung region is precisely marked with internal and external markers. The markers are combined with the gradient image of the(More)
BACKGROUND Numerous functional genomics approaches have been developed to study the model organism yeast, Saccharomyces cerevisiae, with the aim of systematically understanding the biology of the cell. Some of these techniques are based on yeast growth differences under different conditions, such as those generated by gene mutations, chemicals or both.(More)
An application of wavelet packet is presented for electrocardiogram (ECG) and magnetic resonance spectroscopy (MRS) characteristics detection in this study. A fully automated system is developed to detect the "R" peaks which are beat designators and are used consequently to locate other ECG characteristics. They include "P", "Q", "S" and "T" waves along(More)
PURPOSE A fast and robust algorithm was developed for automatic segmentation of the left ventricular endocardial boundary in echocardiographic images. The method was applied to calculate left ventricular volume and ejection fraction estimation. METHODS A fast adaptive B-spline snake algorithm that resolves the computational concerns of conventional active(More)
PURPOSE Compensation for brain shift is often necessary for image-guided neurosurgery, requiring registration of intra-operative ultrasound (US) images with preoperative magnetic resonance images (MRI). A new image similarity measure based on residual complexity (RC) to overcome challenges of registration of intra-operative US and preoperative MR images was(More)
A suspected metabolic brain disorder presents a difficult challenge to the physician and the patient. We have developed a fully automated system in order to classify the Magnetic Resonance Spectroscopy (MRS) signals. Novel fuzzy rules and a fuzzy classifier have been designed in this study to categorize metabolic brain diseases in children. The sensitivity(More)