Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018; 21st International C Alejandro F. Frangi,Julia A. Schnabel,Gabor

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synovitis

Instance Segmentation and Tracking with Cosine Embeddings and Recurrent Hourglass Networkse a novel recurrent fully convolutional network architecture for tracking such instance segmentations over time. The network architecture incorporates convolutional gated recurrent units (ConvGRU) into a stacked hourglass network to utilize temporal video information. Furthermore, we train the netwo

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Skin Lesion Classification in Dermoscopy Images Using Synergic Deep Learninggh deep learning has shown proven advantages over traditional methods, which rely on handcrafted features, in image classification, it remains challenging to classify skin lesions due to the significant intra-class variation and inter-class similarity. In this paper, we propose a synergic deep learn

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enterprise

-Hemolysis Detection on Cultured Blood Agar Plates by Convolutional Neural Networksion diagnostic images representing bacteria colonies on culturing plates. In this context, the presence of .-hemolysis is a key diagnostic sign to assess the presence and virulence of pathogens like streptococci and to characterize major respiratory tract infections. Since it can manifest in a high

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A Pixel-Wise Distance Regression Approach for Joint Retinal Optical Disc and Fovea Detectiony the optic disc and the fovea. For that, instead of attempting to classify each pixel as belonging to the background, the optic disc, or the fovea center, which would lead to a highly class-imbalanced setting, the problem is reformulated as a pixelwise regression task. The regressed quantity consis

植物学

Deep Random Walk for Drusen Segmentation from Fundus Imagesarns deep representations from fundus images and specify an optimal pixel-pixel affinity. Specifically, the proposed architecture is mainly composed of three parts: a deep feature extraction module to learn both semantic-level and low-level representation of image, an affinity learning module to get

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Retinal Artery and Vein Classification via Dominant Sets Clustering-Based Vascular Topology Estimati spectrum of diseases. In this paper, we have proposed a novel framework that is capable of making the artery/vein (A/V) distinction in retinal color fundus images. We have successfully adapted the concept of . and formalize the retinal vessel topology estimation and the A/V classification problem a

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Towards a Glaucoma Risk Index Based on Simulated Hemodynamics from Fundus Imagesthough other biomarkers are being explored to improve the understanding of the pathophysiology of the disease. It has been recently observed that glaucoma induces changes in the ocular hemodynamics. However, its effects on the functional behavior of the retinal arterioles have not been studied yet.

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A Framework for Identifying Diabetic Retinopathy Based on Anti-noise Detection and Attention-Based Fa few tiny lesions which are difficult to perceive even to human experts. Using annotations in the form of lesion bounding boxes may help solve the problem by deep learning models, but fully annotated samples of this type are usually expensive to obtain. Missing annotated samples (i.e., true lesions