Mohamed Bedoui Hedi

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Being able to analyze and interpret signal coming from electroencephalogram (EEG) recording can be of high interest for many applications including medical diagnosis and Brain-Computer Interfaces. Indeed, human experts are today able to extract from this signal many hints related to physiological as well as cognitive states of the recorded subject and it(More)
Accurate coronary artery segmentation is a fundamental step in various medical imaging applications such as stenosis detection, 3D reconstruction and cardiac dynamics assessing. In this paper, a multiscale region growing (MSRG) method for coronary artery segmentation in 2D X-ray angiograms is proposed. First, a region growing rule incorporating both(More)
The development of hardware platforms for artificial neural networks (ANN) has been hindered by the high consumption of power and hardware resources. In this paper, we present a methodology for ANN-optimized implementation, of a learning vector quantization (LVQ) type on a field-programmable gate array (FPGA) device. The aim was to provide an intelligent(More)