Pseudoprogression prediction in high grade primary CNS tumors by use of radiomics
Pseudoprogression prediction in high grade primary CNS tumors by use of radiomics
About this item
Full title
Author / Creator
Ari, Asena Petek , Akkurt, Burak Han , Musigmann, Manfred , Mammadov, Orkhan , Blömer, David A. , Kasap, Dilek N. G. , Henssen, Dylan J. H. A. , Nacul, Nabila Gala , Sartoretti, Elisabeth , Sartoretti, Thomas , Backhaus, Philipp , Thomas, Christian , Stummer, Walter , Heindel, Walter and Mannil, Manoj
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
Formats
Publication information
Publisher
London: Nature Publishing Group UK
Subjects
More information
Scope and Contents
Contents
Our aim is to define the capabilities of radiomics and machine learning in predicting pseudoprogression development from pre-treatment MR images in a patient cohort diagnosed with high grade gliomas. In this retrospective analysis, we analysed 131 patients with high grade gliomas. Segmentation of the contrast enhancing parts of the tumor before adm...
Alternative Titles
Full title
Pseudoprogression prediction in high grade primary CNS tumors by use of radiomics
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_929840dbb9ca48e6a284e427b83fcfee
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_929840dbb9ca48e6a284e427b83fcfee
Other Identifiers
ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-022-09945-9
