Medical Imaging 2023: Image Processing 2023
DOI: 10.1117/12.2653970
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Deep learning-based multi-organ CT segmentation with adversarial data augmentation

Abstract: In this work, we propose an adversarial attack-based data augmentation method to improve the deep-learning-based segmentation algorithm for the delineation of Organs-At-Risk (OAR) in abdominal Computed Tomography (CT) to facilitate radiation therapy. We introduce Adversarial Feature Attack for Medical Image (AFA-MI) augmentation, which forces the segmentation network to learn out-of-distribution statistics and improve generalization and robustness to noises. AFA-MI augmentation consists of three steps: 1) gene… Show more

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