Exploratory study to identify radiomics classifiers for lung cancer histology

Exploratory study to identify radiomics classifiers for lung cancer histology

Background: Radiomics can quantify tumor phenotypic characteristics non-invasively by applying feature algorithms to medical imaging data. In this study of lung cancer patients, we investigated the association between radiomic features and the tumor histologic subtypes (adenocarcinoma and squamous c...

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Bibliographic Details
Main Authors: Weimiao eWu, Chintan eParmar, Patrick eGrossmann, John eQuackenbush, Philippe eLambin, Johan eBussink, Raymond eMak, Hugo eAerts
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-03-01
Series:Frontiers in Oncology
Subjects:
computational science
Feature Selection
quantitative imaging
Lung cancer histology
Radiomics
Online Access:http://journal.frontiersin.org/Journal/10.3389/fonc.2016.00071/full

Internet

http://journal.frontiersin.org/Journal/10.3389/fonc.2016.00071/full

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