Miguel Coimbra

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Life scientists often must count cells in microscopy images, which is a tedious and time-consuming task. Automatic approaches present a solution to this problem. Several procedures have been devised for this task, but the majority suffer from performance degradation in the case of cell overlap. In this article, we propose a method to determine the positions(More)
Most work done in Heart Sound Segmentation approaches use a threshold-based approach to correctly identify S1 and S2 segments in a given signal. We propose a new method that uses the Stationary Wavelet Transform to segment the signal and hierarchical clustering to distinguish the S1 and S2 heart sound from noise. This approach was tested in the Classifying(More)
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