Framework for machine learning of ct and pet radiomics to predict local failure after radiotherapy in locally advanced head and neck cancers

Framework for machine learning of ct and pet radiomics to predict local failure after radiotherapy in locally advanced head and neck cancers

Context: Cancer Radiomics is an emerging field in medical imaging and refers to the process of converting routine radiological images that are typically qualitatively interpreted to quantifiable descriptions of the tumor phenotypes and when combined with statistical analytics can improve the accurac...

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Bibliographic Details
Main Authors: Devadhas Devakumar, Goutham Sunny, Krishna Balu, Stephen R Bowen, Ambily Nadaraj, L Jeyseelan, Manu Mathew, Aparna Irodi, Rajesh Isiah, Simon Pavamani, Subhashini John, Hannah Mary T. Thomas
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2021-01-01
Series:Journal of Medical Physics
Subjects:
computed tomography
head and neck cancer
local failure
machine learning
positron emission tomography
radiomics
Online Access:http://www.jmp.org.in/article.asp?issn=0971-6203;year=2021;volume=46;issue=3;spage=181;epage=188;aulast=Devakumar

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http://www.jmp.org.in/article.asp?issn=0971-6203;year=2021;volume=46;issue=3;spage=181;epage=188;aulast=Devakumar

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