Visualizing histopathologic deep learning classification and anomaly detection using nonlinear feature space dimensionality reduction

Visualizing histopathologic deep learning classification and anomaly detection using nonlinear feature space dimensionality reduction

Abstract Background There is growing interest in utilizing artificial intelligence, and particularly deep learning, for computer vision in histopathology. While accumulating studies highlight expert-level performance of convolutional neural networks (CNNs) on focused classification tasks, most studi...

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Bibliographic Details
Main Authors: Kevin Faust, Quin Xie, Dominick Han, Kartikay Goyle, Zoya Volynskaya, Ugljesa Djuric, Phedias Diamandis
Format: Article
Language:English
Published: BMC 2018-05-01
Series:BMC Bioinformatics
Subjects:
Digital pathology
Deep learning
Convolutional neural networks
t-SNE
Diagnostics
Neuropathology
Online Access:http://link.springer.com/article/10.1186/s12859-018-2184-4

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http://link.springer.com/article/10.1186/s12859-018-2184-4

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