CT Male Pelvic Organ Segmentation via Hybrid Loss Network with Incomplete Annotation

    Dong Nie
    Dong Nie
    Liangqiong Qu
    Liangqiong Qu
    Yeqin Shao
    Yeqin Shao

    IEEE Transactions on Medical Imaging, pp. 2151-2162, 2020.

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    Keywords:
    Image segmentationAnnotationsComputed tomographyBiological systemsBiomedical imagingMore(2+)

    Abstract:

    Sufficient data with complete annotation is essential for training deep models to perform automatic and accurate segmentation of CT male pelvic organs, especially when such data is with great challenges such as low contrast and large shape variation. However, manual annotation is expensive in terms of both finance and human effort, which ...More

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