Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2019; 22nd International C Dinggang Shen,Tianming Liu,Ali Khan Conferen

发生

Data-Driven Enhancement of Blurry Retinal Images via Generative Adversarial Networksagnosis for both ophthalmologists and automatic aided system. Inspired by the great success of generative adversarial networks, a data-driven approach is proposed to enhance the blurry images in a weakly supervised manner. That is to say, instead of paired blurry and high-quality images, our approac

Dealing

Dual Encoding U-Net for Retinal Vessel Segmentationlood vessels requires both sizeable receptive field and rich spatial information. In this paper, we propose a novel Dual Encoding U-Net (DEU-Net), which have two encoders: a spatial path with large kernel to preserve the spatial information and a context path with multiscale convolution block to cap

CURL

A Deep Learning Design for Improving Topology Coherence in Blood Vessel Segmentationve been applied to supervised segmentation of blood vessels, mainly the retinal ones due to the availability of manual annotations. Despite their success, they typically minimize the Binary Cross Entropy loss, which does not penalize topological mistakes. These errors are relevant in graph-like stru

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Unsupervised Ensemble Strategy for Retinal Vessel Segmentationrch considers how to ensemble their results to fully exploit the advantages of each method. In this work, we propose a novel unsupervised ensemble strategy to automatically combine multiple segmentation results for an accurate result. There is a no-reference network that could assess the vessel segm

Intercept

Fully Convolutional Boundary Regression for Retina OCT Segmentationg smooth continuous layer surfaces, with correct hierarchy (topology) are desired for monitoring disease progression. State-of-the-art methods use a trained classifier to label each pixel into background, layer, or surface pixels. The final step of extracting the desired smooth surfaces with correct

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PM-Net: Pyramid Multi-label Network for Joint Optic Disc and Cup Segmentation OD and OC inside the optic nerve head (ONH) area but paying little attention to accurate ONH localization. In this paper, we propose a Mask-RCNN based paradigm to localize ONH and jointly segment OD and OC in a whole fundus image. However, directly using Mask-RCNN faces some critical issues: First,

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Biological Age Estimated from Retinal Imaging: A Novel Biomarker of Agingly. Recently, a new type of BA - ‘brain age’ predicted from brain neuroimaging has been proved to be a novel effective biomarker of aging. The retina is considered to share anatomical and physiological similarities with the brain, and rich information related with aging can be visualized non-invasiv

有限

Task Adaptive Metric Space for Medium-Shot Medical Image Classificationearning has become an important approach to few-shot image classification. However, current research on meta-learning focuses on learning from a few examples; we propose to extend few-shot learning to medium-shot to evaluate medical classification tasks in a more realistic setup. We build a baseline

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