title: Image corruption detection in diffusion tensor imaging for post-processing and real-time monitoring.
abstract: Due to the high sensitivity of diffusion tensor imaging (DTI) to physiological motion, clinical DTI scans often suffer a significant amount of artifacts. Tensor-fitting-based, post-processing outlier rejection is often used to reduce the influence of motion artifacts. Although it is an effective approach, when there are multiple corrupted data, this method may no longer correctly identify and reject the corrupted data. In this paper, we introduce a new criterion called "corrected Inter-Slice Intensity Discontinuity" (cISID) to detect motion-induced artifacts. We compared the performance of algorithms using cISID and other existing methods with regard to artifact detection. The experimental results show that the integration of cISID into fitting-based methods significantly improves the retrospective detection performance at post-processing analysis. The performance of the cISID criterion, if used alone, was inferior to the fitting-based methods, but cISID could effectively identify severely corrupted images with a rapid calculation time. In the second part of this paper, an outlier rejection scheme was implemented on a scanner for real-time monitoring of image quality and reacquisition of the corrupted data. The real-time monitoring, based on cISID and followed by post-processing, fitting-based outlier rejection, could provide a robust environment for routine DTI studies.
authors.affiliation: The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America ; Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
authors.forename: Yue
authors.initials: Y
authors.lastname: Li
authors.forename: Steven M
authors.initials: SM
authors.lastname: Shea
authors.forename: Christine H
authors.initials: CH
authors.lastname: Lorenz
authors.forename: Hangyi
authors.initials: H
authors.lastname: Jiang
authors.forename: Ming-Chung
authors.initials: MC
authors.lastname: Chou
authors.forename: Susumu
authors.initials: S
authors.lastname: Mori
mesh_terms: D016477:Artifacts; D001921:Brain / Q000473:pathology; D056324:Diffusion Tensor Imaging / Q000379:methods* / Q000592:standards*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D009038:Motion; D012372:ROC Curve; D015203:Reproducibility of Results