401 Deepheartct: A Fully Automatic Hybrid Structure Segmentation Framework Based On Atlas, Reverse Ranking, And Convolutional Neural Network For Computed Tomography Angiography

      Introduction: Cardiac computed tomography angiography (CTA) opens new opportunities on image analysis for diagnosing cardiovascular disease. Manual delineation remains the main method to quantify different chambers on CTA images. Deep learning (DL) methods have shown great promise in medical image analysis. However, DL requires large and high-quality training labels which are often limited due to its labor intensive nature. We aim to develop a fully automatic artificial intelligence system based on an optimal computer-labeled dataset for accurate CTA segmentation.
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