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Edge-Sensitive Left Ventricle Segmentation Using Deep Reinforcement Learning
2021
Sensors
Deep reinforcement learning (DRL) has been utilized in numerous computer vision tasks, such as object detection, autonomous driving, etc. However, relatively few DRL methods have been proposed in the area of image segmentation, particularly in left ventricle segmentation. Reinforcement learning-based methods in earlier works often rely on learning proper thresholds to perform segmentation, and the segmentation results are inaccurate due to the sensitivity of the threshold. To tackle this
doi:10.3390/s21072375
pmid:33805558
pmcid:PMC8037138
fatcat:lgrr7s7kczdc5enthydpyh2exm