Imagerie cérébrale : Traitement et Modélisation Embarqués

Abstract : Epilepsy is a chronic pathology defined by the repetition of clinical paroxysmal manifestations called crises. These crises are the result of a generalized or focal brain dysfunction due to an abnormal electrical discharge. The electroencephalography (EEG) is the reference method allowing the recording of the electrical activity of the brain. During an epileptic crisis, EEG signals are of sinusoidal nature and characterized by a high intensity. Generator of the EEG signals, the neuronal populations sync to create a dynamic system. The changes of the oscillations state of the EEG signals, variables over the time, passage of a stable state to an unstable state, reflect the beginning of an epileptic crisis.The conceptual framework of this thesis describes the objective to propose a new approach to predict the occurrence of epileptic crisis and localize the cortical generators associated with the minimum of cranial electrodes. This approach allows alerting the patient and his entourage so that they can take necessary precautions.To ensure early detection of the crisis onset and a precise location of its focuses, we propose a reliable method based firstly on the Multivariate Autoregressive modeling of EEG signals. This modeling generates coefficients capable to describe early changes in the dynamic system state. A Principal Components Analysis based on the extraction of values own of the system has been used to calculate an index of stability. The temporal variation of this index is used to determine the stability of system before, during and after epilepsy and to detect any paroxysmal abnormalities precritical. Our main contributions are as follows:- The Autoregressive Modeling and stability analysis for the early detection occurrence of seizures by using a minimum number of cranial EEG electrodesThe proposed methodology has four main phases: a pretreatment adapted to improve the quality of the signal, an extraction of the relevant parameters of the autoregressive model, a calculation of the stability index and the analysis of crises periods.The reliability of our method and the relevance of our results have been proved by comparing them with other methods reported by the state of the art and validated on the same database (CHB-MIT).-Best spatiotemporal localization of epileptic electric discharge regions on the cortex, following the improvement of the surface resolution of the EEG by the integration of virtual electrodesElectrical discharges are born in the points of the cerebral cortex and propagated to other points in the same hemisphere or of the other hemisphere. The monitoring of the spread of these discharges allows controlling the state of consciousness of the patient. The study that has been conducted is to locate the brain regions involved in the crisis reliably and precisely and monitoring their evolution over time. This study consists of three main phases:In a third phase, the spatiotemporal evolution of the epileptic discharges detected by the electrodes makes it possible to evaluate the patient's condition and to predict possible alterations in consciousness. In the case of an epileptic electric discharge of the fronto-temporal lobe or of several regions on the two hemispheres, the patient passes through a momentary alteration of consciousness
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Ibtissem Khouaja. Imagerie cérébrale : Traitement et Modélisation Embarqués. Imagerie médicale. Université Paris-Est, 2017. Français. ⟨NNT : 2017PESC1120⟩. ⟨tel-01741479v2⟩

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