Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data.
We present an approach for fully automatic urinary bladder segmentation in CT images with artificial neural networks in this study. Automatic medical image analysis has become an invaluable tool in the different treatment stages of diseases. Especially medical image segmentation plays a vital role,...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2019-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0212550 |