Convolutional sparse kernel network for unsupervised medical image analysis
Abstract
The availability of large-scale annotated image datasets and recent advances in supervised deep learning methods enable the end-to-end derivation of representative image features that can impact a variety of image analysis problems. Such supervised approaches, however, are difficult to implement in the medical domain where large volumes of labelled data are difficult to obtain due to the complexity of manual annotation and inter- and...
Paper Details
Title
Convolutional sparse kernel network for unsupervised medical image analysis
Published Date
Aug 1, 2019
Journal
Volume
56
Pages
140 - 151
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