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Titlebook: Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017; 20th International C Maxime Descoteaux,Lena Maier-Hein,Simon Duch

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Geoffrey Jones,Neil T. Clancy,Xiaofei Du,Maria Robu,Simon Arridge,Daniel S. Elson,Danail Stoyanov
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Semi-supervised Segmentation of Optic Cup in Retinal Fundus Images Using Variational Autoencoderides the feature embedding of the images which allows the clustering of the related observation in the latent feature space. We combine the feature embedding with the segmentation autoencoder which is trained on the labeled images for pixel-wise segmentation of the cup region. The main novelty of th
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Quality Assessment of Retinal Hyperspectral Images Using SURF and Intensity Featuresspectral Retinal Camera based on a tuneable light source in the visible and near infrared spectral range (450–900 nm). Compared with the ratings of two observers, our proposed method shows encouraging results in artifact detection and quality assessment.
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Accurate Correspondence of Cone Photoreceptor Neurons in the Human Eye Using Graph Matching Applied cone packing information to determine the correspondence of repeated imaging of cone photoreceptor neurons across longitudinal AOSLO datasets. The matching framework was evaluated on imaging data from ten subjects using a validation dataset created by removing 15% of the neurons from 713 neuron cor
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