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

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Mhc-Molecule

Enhancing OCT Signal by Fusion of GANs: Improving Statistical Power of Glaucoma Clinical Trialstical coherence tomography (SDOCT) is now in widespread clinical use, past landmark glaucoma clinical trials have used time-domain optical coherence tomography (TDOCT), which leads, however, to poor statistical power due to low signal-to-noise characteristics. Here, we propose a probabilistic ensemb

dura-mater

A Deep Reinforcement Learning Framework for Frame-by-Frame Plaque Tracking on Intravascular Optical A continuous and accurate plaque tracking algorithm is critical for coronary heart disease diagnosis and treatment. However, continuous and accurate plaque tracking frame-by-frame is very challenging because of some difficulties from IVOCT imaging conditions, such as speckle noise, complex and vari

phase-2-enzyme

visual-cortex

Retinal Abnormalities Recognition Using Regional Multitask Learningp learning based automatic screening generally focused on specific types of retinal diseases, such as diabetic retinopathy and glaucoma. Since patients may suffer from various types of retinal diseases simultaneously, these solutions are not clinically practical. To address this issue, we propose a

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amygdala

3D Surface-Based Geometric and Topological Quantification of Retinal Microvasculature in OCT-Angiogrworks have been mainly focusing on the microvascular analysis of 2D enface OCT-A projections while direct 3D analysis using rich depth-resolved microvascular information is rarely considered. In this work, we aim to set up an innovative 3D microvascular modeling framework via Reeb analysis to explor

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