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Valentin Ogrean and Remus Brad
Since their inception, deep-learning architectures have shown promising results for automatic segmentation. However, despite the technical advances introduced by fully convolutional networks, generative adversarial networks or recurrent neural networks, ...
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Junkang Qin, Xiao Wang, Dechang Mi, Qinmu Wu, Zhiqin He and Yu Tang
The study of human torso medical image segmentation is significant for computer-aided diagnosis of human examination, disease tracking, and disease prevention and treatment. In this paper, two application tasks are designed for torso medical images: the ...
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Jialin Shi, Chenyi Guo and Ji Wu
Deep-learning models require large amounts of accurately labeled data. However, for medical image segmentation, high-quality labels rely on expert experience, and less-experienced operators provide noisy labels. How one might mitigate the negative effect...
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