Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring.

IEEE Transactions on Medical Imaging(2016)

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摘要
Mammographic risk scoring has commonly been automated by extracting a set of handcrafted features from mammograms, and relating the responses directly or indirectly to breast cancer risk. We present a method that learns a feature hierarchy from unlabeled data. When the learned features are used as the input to a simple classifier, two different tasks can be addressed: i) breast density segmentatio...
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关键词
Breast cancer,Computer architecture,Machine learning,Mammography,Manuals,Image segmentation
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