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Paleness or pallor is a manifestation of blood loss or low hemoglobin concentrations in the human blood that can be caused by pathologies such as anemia. This work presents the first automated screening system that utilizes pallor site images, segments, and extracts color and intensity-based features for multi-class classification of patients with high pallor due to anemia-like pathologies, normal...
Convolutional Neural Networks (CNN) are useful methods for identification of previously unknown embedded patterns in images. Several object and facial recognition along with image segmentation tasks have benefited from the non-linear abstraction of hybrid features using CNN. This work presents a novel CNN model parametrization work-flow developed on the cloud-computing platform of Microsoft Azure...
With the increasing applications of Big Data analytics in medical image processing systems, there has been a growing need for quantitative medical image quality assessment techniques. Specifically for computed tomography (CT) images, quantitative image assessment can allow for benchmarking image processing methods and optimization of image acquisition parameters. In this work, large volumes of CT...
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