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Brain magnetic resonance imaging (MRI) in patients with Multiple Sclerosis (MS) shows regions of signal abnormalities, named plaques or lesions. The spatial lesion distribution plays a major role for MS diagnosis. In this paper we present a 3D MS-lesion segmentation method based on an adaptive geometric brain model. We model the topological properties of the lesions and brain tissues in order to constrain...
Heart failure and heart valvar diseases are chronic heart disorders which are potentially diagnosed using heart sound characteristics. Heart sound components S1 and S2 exhibit significant characteristics for valvar dysfunction while pathological S3 sound is a prominent sign for heart failure in elderly people. In this paper, a new automatic detection method of the S3 heart sound is proposed. The method...
An integrated framework for ventricular arrhythmias (VA) assessment, composed of two levels, is proposed in this work. The first level consists of four independent neural networks (NN), designed for specific detection tasks: signal quality, premature ventricular contractions (PVC), ventricular tachycardia (VT) and ventricular fibrillation (VF). Time and frequency domain features, obtained from the...
A new unsupervised and low complexity method for detection of S1 and S2 components of heart sound without the ECG reference is described The most reliable and invariant feature applied in current state-of-the-art of unsupervised heart sound segmentation algorithms is implicitly or explicitly the S1-S2 interval regularity. However; this criterion is inherently prone to noise influence and does not...
Optical mapping has become an important technique in the study of cardiac electrophysiology, especially in terms of investigating the mechanisms of cardiac arrhythmias. The increasing availability of transgenic mice as models for cardiovascular disease is driving the need for instrumentation suitable for the study of electrical activity in the mouse heart. In this paper we evaluate our optical mapping...
Innovative concepts for prevention and disease management of cardio-vascular disease are being developed in the framework of MyHeart project. After a successful first phase where 16 different concepts were tested, four of them where selected on the basis of user acceptance, technical feasibility and foreseen impact. The present paper gives an overview of such product-concepts that are being implemented...
A new unsupervised and low complexity method for detection of S1 and S2 components of heart sound without the ECG reference is described The most reliable and invariant feature applied in current state-of-the-art of unsupervised heart sound segmentation algorithms is implicitly or explicitly the S1-S2 interval regularity. However; this criterion is inherently prone to noise influence and does not...
This paper is aimed at the identification of the boundaries of murmur present in heart sound. Heart murmurs provide crucial diagnosis information for several heart diseases such as natural or prosthetic valve dysfunction and heart failure. In order to find the valuable information about abnormal heart behavior, segmentation of the heart murmurs has to be performed. In this work we solve this problem...
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