Superpixel-Based Conditional Random Fields (SuperCRF): Incorporating Global and Local Context for Enhanced Deep Learning in Melanoma Histopathology

Superpixel-Based Conditional Random Fields (SuperCRF): Incorporating Global and Local Context for Enhanced Deep Learning in Melanoma Histopathology

Computational pathology-based cell classification algorithms are revolutionizing the study of the tumor microenvironment and can provide novel predictive/prognosis biomarkers crucial for the delivery of precision oncology. Current algorithms used on hematoxylin and eosin slides are based on individu...

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Bibliographic Details
Main Authors: Konstantinos Zormpas-Petridis, Henrik Failmezger, Shan E Ahmed Raza, Ioannis Roxanis, Yann Jamin, Yinyin Yuan
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-10-01
Series:Frontiers in Oncology
Subjects:
deep learning
machine learning
conditional random fields
digital pathology
cell classification
melanoma
Online Access:https://www.frontiersin.org/article/10.3389/fonc.2019.01045/full

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https://www.frontiersin.org/article/10.3389/fonc.2019.01045/full

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