Titlebook: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016; 19th International C Sebastien Ourselin,Leo Joskowicz,William Wel

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Multimodal Deep Learning for Cervical Dysplasia Diagnosis, However, current multimodal frameworks suffer from low sensitivity at high specificity levels, due to their limitations in learning correlations among highly heterogeneous modalities. In this paper, we design a deep learning framework for cervical dysplasia diagnosis by leveraging multimodal inform

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Deep Retinal Image Understanding, disc segmentation. We make use of deep Convolutional Neural Networks (CNNs), which have proven revolutionary in other fields of computer vision such as object detection and image classification, and we bring their power to the study of eye fundus images. DRIU uses a base network architecture on whi

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enchant

Deep Neural Networks for Fast Segmentation of 3D Medical Images, image classification and semantic segmentation. In this paper, a CNN for 3D volume segmentation based on recently introduced deep learning components will be presented. In addition to using image patches as input for a CNN, the usage of orthogonal patches, which combine shape and locality informati

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