Learn More
This paper presents the results of morphological heart arrhythmia detection based on features of electrocardiography, ECG, signal. These signals are obtained from MIT/BIH arrhythmia database. The ECG beats were first modeled using Hermitian basis functions, (HBF). In this step, the width parameter, sigma, of HBF was optimized to minimize the model error.(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 the results of morphological heart arrhythmia detection based on parameters which are obtained from modeling of the cumulants of the electrocardiography, ECG, signals. Cumulants possess many properties that make them effective tools to describe morphological variations of non-stationary signals. Among these properties, the two most(More)
In this paper, a new piecewise modeling for approximation of ECG signal is presented. Most of the modeling methods are focused to obtain the best approximation of the entire ECG signal. The proposed method exploits the importance of different intervals of ECG signals, in particular QRS complex, by performing a segmented based modeling using Hermitian basis(More)
The gradient vector flow (GVF) algorithm has been used extensively as an efficient method for medical image segmentation. This algorithm suffers from poor robustness against noise as well as lack of convergence in small scale details and concavities. As a cure to this problem, in this paper the idea of multi scale is applied to the traditional GVF algorithm(More)
Estimation of brain deformation plays an important role in computer-aided therapy and image-guided neurosurgery systems. Tumour growth can cause brain deformation and change stress distribution in the brain. Biomechanical models exist that use a finite element method to estimate brain shift caused by tumour growth. Such models can be categorised as linear(More)
Intra-operative brain deformation (brain shift) limits the accuracy of image-guided neuro-surgery systems. Ultrasound imaging as a simple, fast and being real time has become an alternative to MR imaging which is an expensive system for brain shift calculation. The main challenges due to speckle noise and artifacts in US images, is to perform an accurate(More)
PURPOSE The presence of metallic dental fillings is prevalent in head and neck PET/CT imaging and generates bright and dark streaking artifacts in reconstructed CT images. The resulting artifacts would propagate to the corresponding PET images following CT-based attenuation correction (CTAC). This would cause over- and/or underestimation of tracer uptake in(More)
OBJECTIVE Hybrid PET/MRI presents many advantages in comparison with its counterpart PET/CT in terms of improved soft-tissue contrast, decrease in radiation exposure, and truly simultaneous and multi-parametric imaging capabilities. However, the lack of well-established methodology for MR-based attenuation correction is hampering further development and(More)
In this work, we have developed and evaluated an electrocardiogram (ECG) feature extraction system based on the multi-resolution wavelet transform. ECG signals from Modified Lead II (MLII) are chosen for processing. The result of applying two wavelet filters (D4 and D6) of different length on the signal is compared. The wavelet filter with scaling function(More)