Efficient Semi-supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency

Xiangde Luo; Wenjun Liao; Jieneng Chen; Tao Song; Yinan Chen; Shichuan Zhang; Nianyong Chen; Guotai Wang; Shaoting Zhang

doi:10.1007/978-3-030-87196-3_30

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Efficient Semi-supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency

Xiangde Luo Wenjun Liao Jieneng Chen Tao Song Yinan Chen Shichuan Zhang Nianyong Chen Guotai Wang Shaoting Zhang

Year: 2021 Lecture notes in computer science Pages: 318-329 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-030-87196-3_30

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Keywords:

Computer science Segmentation Pyramid (geometry) Ground truth Artificial intelligence Robustness (evolution) Pattern recognition (psychology) Consistency (knowledge bases) Image segmentation Pixel Computer vision Mathematics

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Head and Neck Cancer Studies

Health Sciences → Medicine → Otorhinolaryngology

Medical Image Segmentation Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Efficient Semi-supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency

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