Original paper

Sparse autoencoder for unsupervised nucleus detection and representation in histopathology images

Volume: 86, Pages: 188 - 200
Published: Feb 1, 2019
Abstract
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 primary contribution of our work is the development of an unsupervised detection network by using the characteristics of histopathology image patches. The...
Paper Details
Title
Sparse autoencoder for unsupervised nucleus detection and representation in histopathology images
Published Date
Feb 1, 2019
Volume
86
Pages
188 - 200
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