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Feb 25, 2023 · In this work, we propose an adversarial attack-based data augmentation method to improve the deep-learning-based segmentation algorithm for the ...
... adversarial attack-based data augmentation method to improve the deep-learning-based segmentation algorithm for the delineation of Organs-At-Risk (OAR) in ...
In this work, we propose an adversarial attack-based data augmentation method to improve the deep-learning-based segmentation algorithm for the delineation ...
In this paper we present a new segmentation method meant for boost area that remains after removing the tumour using BCT (breast conserving therapy).
Feb 22, 2024 · Abstract. A novel 3D nnU-Net-based of algorithm was developed for fully-automated multi-organ segmentation in abdominal CT, applicable to both ...
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Deep Learning-based Multi-Organ CT Segmentation with Adversarial Data ...
www.x-mol.com › paper › adv
Feb 25, 2023 · In this work, we propose an adversarial attack-based data augmentation method to improve the deep-learning-based segmentation algorithm for ...
Jun 8, 2024 · Accurate segmentation of multiple organs in the head, neck, chest, and abdomen from medical images is an essential step in computer-aided ...
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In this context, we address fully-automated multi-organ segmentation from abdominal CT and MR images using deep learning. The proposed model extends standard ...
A Review of Deep Learning based Methods for Medical Image Multi ...
www.ncbi.nlm.nih.gov › PMC8217246
May 13, 2021 · Performance evaluation of 2D and 3D deep learning approaches for automatic segmentation of multiple organs on CT images. Medical Imaging ...
The objective of CT image segmentation is to extract information about organs of interest and diseased organs. Accurate segmentation is essential, as errors can ...