Abstract:Background: Although convolutional neural network (CNN)-based methods have been widely used in medical image analysis and have achieved great success in many medical segmentation tasks, these methods suffer from various imbalance problems, which reduce the accuracy and validity of segmentation results.
Methods:We proposed two simple but effective sample balancing methods, positive-negative subset selection (PNSS) and hard-easy subset selection (HESS) for foreground-to-background imbalance and hardto-easy imbal… Show more
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