Reproducibility and non-redundancy of radiomic features extracted from arterial phase CT scans in hepatocellular carcinoma patients: impact of tumor segmentation variability | Zendy

Qingtao Qiu | Zendy; Jinghao Duan | Zendy; Zuyun Duan | Zendy; Xiangjuan Meng | Zendy; Changsheng Ma | Zendy; Jian Zhu | Zendy; Jie Lu | Zendy; Tonghai Liu | Zendy; Yong Yin | Zendy

Open Access

Reproducibility 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,

Xiangjuan Meng,

Changsheng Ma,

Jian Zhu,

Jie Lu,

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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research