Titlebook: Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics; Le Lu,Xiaosong Wang,Lin Yang Book 2019 Sprin

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Glaucoma Detection Based on Deep Learning Network in Fundus Images based on deep learning?technique. The first is the multi-label?segmentation network, named M-Net, which solves the optic disc and optic cup segmentation jointly. M-Net contains a multi-scale U-shape convolutional network with the side-output layer to learn discriminative representations and produc

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Thoracic Disease Identification and Localization with Limited Supervisionilding a highly accurate prediction model for these tasks usually requires a large number of images manually annotated with labels and finding sites of abnormalities. In reality, however, such annotated data are expensive to acquire, especially the ones with location annotations. We need methods tha

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Deep Reinforcement Learning for Detecting Breast Lesions from DCE-MRI resonance images (DCE-MRI) at state-of-the-art accuracy. In contrast to previous methods based on computationally expensive exhaustive search strategies, our method reduces the inference time with a search approach that gradually focuses on lesions by progressively transforming a bounding volume un

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Deep Spatial-Temporal Convolutional Neural Networks for Medical Image Restorationy and blood flow in virtually live time. However, effective visualization exposes patients to radiocontrast pharmaceuticals and extended scan times. Higher radiation dosage exposes patients to potential risks including hair loss, cataract formation, and cancer. To alleviate these risks, radiation do

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