Exploratory Study to Identify Radiomics Classifiers for Lung Cancer Histology
Main Authors: | Wu, Weimiao, Parmar, Chintan, Grossmann, Patrick, Quackenbush, John, Lambin, Philippe, Bussink, Johan, Mak, Raymond, Aerts, Hugo J. W. L. |
---|---|
Format: | Online |
Language: | English |
Published: |
Frontiers Media S.A.
2016
|
Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4811956/ |
Similar Items
-
Machine Learning methods for Quantitative Radiomic Biomarkers
by: Parmar, Chintan, et al.
Published: (2015) -
Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer
by: Parmar, Chintan, et al.
Published: (2015) -
Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer
by: Parmar, Chintan, et al.
Published: (2015) -
Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
by: Aerts, Hugo J. W. L., et al.
Published: (2014) -
Robust Radiomics Feature Quantification Using Semiautomatic Volumetric Segmentation
by: Parmar, Chintan, et al.
Published: (2014)