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A hybrid multidimensional image segmentation algorithm is proposed, which combines edge and region-based techniques through the morphological algorithm of watersheds. An edge-preserving statistical noise reduction approach is used as a preprocessing stage in order to compute an accurate estimate of the image gradient. Then, an initial partitioning of the(More)
The detection of lumen and media-adventitia borders in intravascular ultrasound (IVUS) images constitutes a necessary step for the quantitative assessment of atherosclerotic lesions. To date, most of the segmentation methods reported are either manual, or semi-automated, requiring user interaction at some extent, which increases the analysis time and(More)
In this paper we propose a combined scheme of linear prediction analysis for feature extraction along with linear projection methods for feature reduction followed by known pattern recognition methods on the purpose of discriminating between normal and pathological voice samples. Two different cases of speech under vocal fold pathology are examined: vocal(More)
— The detection of ischemic cardiac beats from a patient's electrocardiogram (ECG) signal is based on the characteristics of a specific part of the beat called the ST segment. The correct classification of the beats relies heavily on the efficient and accurate extraction of the ST segment features. In the present paper, an algorithm is developed for this(More)
Health delivery practices are shifting towards home care. The reasons are the better possibilities for managing chronic care, controlling health delivery costs, increasing quality of life and quality of health services and the distinct possibility of predicting and thus avoiding serious complications. For the above goals to become routine, new telemedicine(More)
In this paper, a multiagent system (MAS) is presented, aiming to enhance monitoring, surveillance, and educational services of a generic medical contact center (MCC) for chronic disease management. In such a home-care scenario, a persistent need arises for efficiently monitoring the patient contacts and the MCC's functionality, in order to effectively(More)
OBJECTIVES Sensor networks constitute the backbone for the construction of personalized monitoring systems. Up to now, several sensor networks have been proposed for diverse pervasive healthcare applications, which are however characterized by a significant lack of open architectures, resulting in closed, non-interoperable and difficult to extend solutions.(More)
In the context of the Citizen Health System (CHS) project, a modular Medical Contact Center (MCC) was developed, which can be used in the monitoring, treatment, and management of chronically ill patients at home, such as diabetic or congestive heart failure patients. The virtue of the CHS contact center is that, using any type of communication and(More)
This paper introduces a methodology for combining multi-channel psycho-physiological recordings of affective paradigms into a framework where the scientific results of such experiments are utilized in the human computer interaction context to model the computer's response based on the emotional context of the user and the situation. An affective protocol is(More)
In this paper, an ontology-based system (KnowBaSICS-M) is presented for the semantic management of Medical Computational Problems (MCPs), i.e., medical problems and computerised algorithmic solutions. The system provides an open environment, which: (1) allows clinicians and researchers to retrieve potential algorithmic solutions pertinent to a medical(More)