Abstract #4292

Semi-Automated Rejection of Corrupted Images in Cardiac Diffusion Tensor Imaging

Sam Coveney¹, Chris Kelly¹, Irvin Teh¹, Maryam Afzali^1,2, Lars Mueller¹, Arka Das³, Filip Szczepankiewicz⁴, Derek K Jones², Erica Dall’Armellina¹, and Jurgen E Schneider ¹

¹Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom, ²Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom, ³Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom, ⁴Medical Radiation Physics, Clinical Sciences Lund, Lund University, Lund, Sweden

Synopsis

Keywords: Heart, Diffusion Tensor ImagingCardiac Diffusion Tensor Imaging (cDTI) is prone to imaging artefacts including distortion, signal dropout, and misregistration even after post-processing. We developed a method for image rejection based on a comparison between the observed images and the corresponding set of predicted images generated by tensor models fit to the observed data. A rejection threshold to exclude images from subsequent refitting of the tensor model can be chosen by the user with a simple graphical method.

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