Open AccessReproducibility and non-redundancy of radiomic features extracted from arterial phase CT scans in hepatocellular carcinoma patients: impact of tumor segmentation variability
Author(s) -
Qingtao Qiu,
Jinghao Duan,
Zuyun Duan,
Xiangwen Meng,
Changsheng Ma,
Jian Zhu,
Jie Liu,
Tonghai Liu,
Yong Yin
Publication year - 2019
Publication title -
quantitative imaging in medicine and surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.766
H-Index - 21
eISSN - 2223-4292
pISSN - 2223-4306
DOI - 10.21037/qims.2019.03.02
Subject(s) - reproducibility , hepatocellular carcinoma , segmentation , redundancy (engineering) , radiology , medicine , computer science , radiomics , nuclear medicine , artificial intelligence , mathematics , statistics , operating system
The reproducibility and non-redundancy of radiomic features are challenges in accelerating the clinical translation of radiomics. In this study, we focused on the robustness and non-redundancy of radiomic features extracted from computed tomography (CT) scans in hepatocellular carcinoma (HCC) patients with respect to different tumor segmentation methods.