NIMG-70. QUANTITATIVE IMAGE ANALYSIS AND MACHINE LEARNING TECHNIQUES FOR DISTINGUISHING TRUE PROGRESSION FROM PSEUDOPROGRESSION IN PATIENTS WITH GLIOBLASTOMA-Reference-Cited by-同舟云学术

NIMG-70. QUANTITATIVE IMAGE ANALYSIS AND MACHINE LEARNING TECHNIQUES FOR DISTINGUISHING TRUE PROGRESSION FROM PSEUDOPROGRESSION IN PATIENTS WITH GLIOBLASTOMA

Published:2018-11 Issue:suppl_6 Volume:20 Page:vi191-vi192
ISSN:1522-8517
Container-title:Neuro-Oncology
language:en
Short-container-title:

Author:

Akbari Hamed¹,Rathore Saima²,Bakas Spyridon¹,Nasrallah MacLean³,Rozycki Martin¹,Mohan Suyash¹,Wolf Ronald¹,Bilello Michel¹,Martinez-Lage Maria⁴,Davatzikos Christos²

Affiliation:

1. University of Pennsylvania, Philadelphia, PA, USA

2. Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA

3. Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

4. Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

Publisher

Oxford University Press (OUP)

Subject

Cancer Research,Clinical Neurology,Oncology

Link

http://academic.oup.com/neuro-oncology/article-pdf/20/suppl_6/vi191/26280270/noy148.794.pdf

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