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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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| Pubblicato in: | Pattern Recognit |
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| Autori principali: | , , , , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2018
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| Soggetti: | |
| Accesso online: | 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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