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Biomedical subjects

E Bacharakis

Publications and source records attributed to E Bacharakis.

2 recordsLinked to original sources

Integration of digital angiography and gamma-camera diagnostic modalities to a generalized hospital information system.

Within the framework of the NIKA project for the development of a "Generalized System for Processing and Management of Medical Images", we have integrated a Digital Subtraction Angiography (DSA) station and a gamma-camera diagnostic modality to the newly developed generalized hospital-wide information system. The integration consists of acquiring, digitizing, converting and filing the information from the above diagnostic modalities to the hospital's Picture Archiving and Communication System (PACS). The PACS, which is installed in the Onasio Cardiosurgery Centre of Athens, Greece, is responsible for archival, cataloging, retrieval and viewing of the large volume of patient examination data accumulated during his/her stay in the Centre. The ultimate goal is for all patient data, from all different examinations, to be viewed on dedicated client workstations. Information from different modalities can then be simultaneously presented to the attending physician, for a complete picture of the patient history and condition.

Angiography, Digital Subtraction↗

Maternal and foetal ECG separation using blind source separation methods.

The separation of the maternal and foetal electrocardiograms (ECGs) from skin electrodes located on the mother's body may be modelled as a blind source separation (BSS) problem. This consists in the reconstruction of a set of unknown mutually independent source signals from the sole knowledge of another set of linear mixtures of the sources, where the mixture pattern is also unknown. Three BSS methods based on cumulants are considered: principal-component analysis (PCA), higher-order singular-value decomposition (HOSVD), and higher-order eigenvalue decomposition (HOEVD). All these methods are applied to the foetal-ECG extraction problem by using real ECG data. The last two methods appear to provide a more satisfactory separation than the first method, with HOEVD offering slightly better results.

Biomedical Engineering↗