Quantification of the Immune Content in Neuroblastoma: Deep Learning and Topological Data Analysis in Digital Pathology

Quantification of the Immune Content in Neuroblastoma: Deep Learning and Topological Data Analysis in Digital Pathology

We introduce here a novel machine learning (ML) framework to address the issue of the quantitative assessment of the immune content in neuroblastoma (NB) specimens. First, the EUNet, a U-Net with an EfficientNet encoder, is trained to detect lymphocytes on tissue digital slides stained with the CD3...

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Bibliographic Details
Main Authors: Nicole Bussola, Bruno Papa, Ombretta Melaiu, Aurora Castellano, Doriana Fruci, Giuseppe Jurman
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:International Journal of Molecular Sciences
Subjects:
neuroblastoma
digital pathology
classification
deep learning
topological data analysis
Online Access:https://www.mdpi.com/1422-0067/22/16/8804

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