Microvessel prediction in H&E Stained Pathology Images using fully convolutional neural networks

Microvessel prediction in H&E Stained Pathology Images using fully convolutional neural networks

Abstract Background Pathological angiogenesis has been identified in many malignancies as a potential prognostic factor and target for therapy. In most cases, angiogenic analysis is based on the measurement of microvessel density (MVD) detected by immunostaining of CD31 or CD34. However, most retrie...

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Bibliographic Details
Main Authors: Faliu Yi, Lin Yang, Shidan Wang, Lei Guo, Chenglong Huang, Yang Xie, Guanghua Xiao
Format: Article
Language:English
Published: BMC 2018-02-01
Series:BMC Bioinformatics
Subjects:
Pathology image
H&E images
Angiogenesis
Microvessel
Fully convolutional neural networks
Online Access:http://link.springer.com/article/10.1186/s12859-018-2055-z

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http://link.springer.com/article/10.1186/s12859-018-2055-z

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