Effects of Reconstruction Filter Kernels in Computed Tomography on Radiomic Image Features

被引:0
|
作者
Sweetland, Katharine [1 ]
Chu, Karen [1 ]
Lei, Xiaomeng [2 ]
Cen, Steven Y. [2 ]
Duddalwar, Vinay A. [3 ]
Varghese, Bino A. [4 ]
Hwang, Darryl H. [3 ]
机构
[1] Univ Southern Calif, Alfred E Mann Dept Biomed Engn, Los Angeles, CA 90007 USA
[2] Univ Southern Calif, Dept Radiol, Keck Sch Med, Los Angeles, CA USA
[3] USC Viterbi Sch Engn, Dept Radiol, USC Keck Sch Med, Alfred E Mann Dept Biomed Engn, Los Angeles, CA USA
[4] USC Keck Sch Med, Dept Radiol, Los Angeles, CA USA
来源
2023 19TH INTERNATIONAL SYMPOSIUM ON MEDICAL INFORMATION PROCESSING AND ANALYSIS, SIPAIM | 2023年
关键词
IBSI; image kernel; reconstruction; radiomics; image feature; biomarker;
D O I
10.1109/SIPAIM56729.2023.10373503
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Radiomic metrics offer a promising quantitative tool for diagnosis. This paper seeks to assess the robustness of International Biomarker Standardization Initiative (IBSI) image features across 58 reconstruction filter kernels employed by the Canon Aquilion One CT scanner. By using volumes generated from the same raw data but different image filter kernels, the radiomic metrics generated solely reflect the differences in scanner image reconstruction. Explored are 5 different tissue regions of interest with 463 IBSI image features. Quantification of the image kernel differences could serve future harmonization algorithms.
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页数:5
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