Sivan Lieberman

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In this work, we examine the strength of deep learning approaches for pathology detection in chest radiographs. Convolutional neural networks (CNN) deep architecture classification approaches have gained popularity due to their ability to learn mid and high level image representations. We explore the ability of CNN learned from a non-medical dataset to(More)
We report a case of hemimegalencephaly diagnosed by prenatal MRI with an emphasis on its appearance on diffusion-weighted images. This case shows that in this condition the enlarged hemisphere may show restricted diffusion on prenatal MRI. In our opinion, this finding may result from a combination of increased cellularity and advanced myelination in the(More)
Daily turnover of cholesterol obtained by the balance method was compared to daily input rates calculated by input-output analysis in 43 experiments. The mean value of input rates for kinetic data of 10.1-16.4 weeks' duration (14 experiments) was 1.05 g/day vs. the chemical turnover of 0.94 g/day (difference 10.9 percent). For decay curves of 4.8-9.9 weeks'(More)
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