Sparse Autoencoder for Unsupervised Nucleus Detection and Representation in Histopathology Images

We propose a sparse Convolutional Autoencoder (CAE) for simultaneous nucleus detection and feature extraction in histopathology tissue images. Our CAE detects and encodes nuclei in image patches in tissue images into sparse feature maps that encode both the location and appearance of nuclei. A prima...

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Vydáno v:Pattern Recognit
Hlavní autoři: Hou, Le, Nguyen, Vu, Kanevsky, Ariel B., Samaras, Dimitris, Kurc, Tahsin M., Zhao, Tianhao, Gupta, Rajarsi R., Gao, Yi, Chen, Wenjin, Foran, David, Saltz, Joel H.
Médium: Artigo
Jazyk:Inglês
Vydáno: 2018
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On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC6322841/
https://ncbi.nlm.nih.gov/pubmed/30631215
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.patcog.2018.09.007
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