Stability of radiomic features of liver lesions from manual delineation in CT scans

Jan Hendrik Moltz

doi:10.1117/12.2512406

13 March 2019 Stability of radiomic features of liver lesions from manual delineation in CT scans

Jan Hendrik Moltz

Proceedings Volume 10950, Medical Imaging 2019: Computer-Aided Diagnosis; 109501W (2019) https://doi.org/10.1117/12.2512406
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

We investigate the stability of radiomic features under variations in manual delineation of liver tumors. The analysis is based on 13 CT scans with ten expert segmentations of a lesion per patient. We computed 110 firstorder, shape, and texture features using the open-source software pyradiomics and created a ranking by intra-class correlation (ICC), discarding highly correlated features. Half of the 27 remaining features have very good stability (ICC > 0.9), with features relating to size, simple texture and average intensity performing best. Elongation and kurtosis are by far the least stable features (ICC < 0.65) and should be avoided.

Conference Presentation

Citation Download Citation

Jan Hendrik Moltz "Stability of radiomic features of liver lesions from manual delineation in CT scans", Proc. SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis, 109501W (13 March 2019); https://doi.org/10.1117/12.2512406

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available