Shape Transformation Driven by Active Contour for Class-Imbalanced Semi-Supervised Medical Image Segmentation

Annotating 3D medical images demands expert knowledge and is time-consuming. As a result, semi-supervised learning (SSL) approaches have gained significant interest in 3D medical image segmentation. The significant size differences among various organs in the human body lead to imbalanced class dist...

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Vydáno v:	Proceedings (IEEE International Conference on Bioinformatics and Biomedicine) s. 1966 - 1973
Hlavní autoři:	Gu, Yuliang, Liu, Yepeng, Sun, Zhichao, Zhu, Jinchi, Xu, Yongchao, Najman, Laurent
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 03.12.2024
Témata:	3D medical image segmentation Active contours Biological systems Biomedical imaging Class imbalance Data augmentation Deformation Image segmentation Level set Semi-supervised learning Shape Three-dimensional displays Training Vectors
ISSN:	2156-1133
On-line přístup:	Získat plný text
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