Abstract #3467

The repeatability of IVIM with fuzzy clustering algorithm in liver imaging

Kaining Shi¹, Ying Liu², Yu Shi², and Qiyong Guo²

¹Imaging Systems Clinical Science, Philips Healthcare, Beijing, China, People's Republic of, ²Radiology department, Shengjing Hospital of China Medical University, Shenyang, China, People's Republic of

Fussy clustering technique (FCM) has been combined with IVIM to increase the stability and reduce the post-processing time of the nonlinear curve fitting in IVIM. Another problem of the widely used bi-exponential IVIM model is its poor repeatability. This work is to assess the repeatability of IVIM with FCM between two scans in healthy liver by calculating the coefficient of variation and the 95% Bland–Altman limits of agreements. Results proved that FCM could improve the repeatability of IVIM, especially for the parameter D*, which was the most unstable among total 3 parameters.

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