Open AccessMachine learning-based detection of aberrant deep learning segmentations of target and organs at risk for prostate radiotherapy using a secondary segmentation algorithm
Author(s) -
Michaël Claessens,
Verdi Vanreusel,
Geert De Kerf,
Isabelle Mollaert,
Fredrik Löfman,
Mark J. Gooding,
Charlotte L. Brouwer,
Piet Dirix,
Dirk Verellen
Publication year - 2022
Publication title -
physics in medicine and biology/physics in medicine and biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.312
H-Index - 191
eISSN - 1361-6560
pISSN - 0031-9155
DOI - 10.1088/1361-6560/ac6fad
Subject(s) - segmentation , computer science , artificial intelligence , usability , quality assurance , correctness , contouring , prostate , machine learning , pattern recognition (psychology) , medicine , algorithm , pathology , external quality assessment , computer graphics (images) , human–computer interaction , cancer