Abstract #5325

Comparison of Different Methods for Motion-induced Data Corruption Detection Using k-space Information in Diffusion Imaging

Zhe Zhang^1,2, Hua Guo², Zhangxuan Hu², Yaou Liu^1,3, Yilong Wang^4,5, and Chun Yuan^1,2,6

¹Tiantan Image Research Center, China National Clinical Research Center for Neurological Diseases, Beijing, China, ²Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, ³Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China, ⁴Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China, ⁵China National Clinical Research Center for Neurological Diseases, Beijing, China, ⁶Department of Radiology, University of Washington, Seattle, WA, United States

In diffusion imaging, subject motion together with diffusion encoding gradient may introduce data corruption. Several methods for corrupted data detection using k-space information such as DC peak amplitude, entropy and signal distribution metric have been proposed, and the detection directly from acquired k-space enables instant data rejection and re-acquisition. This work compared and evaluated these methods using the same single-shot data set. The results show that all methods can successfully detect corrupted shots, and demonstrate good detection consistency with each other and also with ADC measurement.

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