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Deep learning has shown great success in high-level image analysis problems;yet its efficacy relies on the quality and diversity of the training data. Inthis work, we introduce a copypaste image augmentation for ultrasound images.The Poisson image editing technique is used to generate realistic and seamlessboundary transitions around the pasted image. Results showed that the proposedimage augmentation technique improves training performance in terms of higherobjective metrics and more stable training results.

Copy-Paste Image Augmentation with Poisson Image Editing for Ultrasound Instance Segmentation Learning