Evaluation of Variable-TE computed Diffusion Weighted Imaging Technique using Deep Learning based Noise Reduction

In this study to the authors adapted the variable-TE cDWI(vTE-cDWI) technique applying denoise approach with deep learning reconstruction(dDLR) to the abdominal region, using ADC-map, T2-map and T1-map with IR-based images. The algorithm under evaluation allows computing diffusion images for arbitrary combinations of TE, b-value and TI based on four acquisitions(4-points method). This technique was shown to generate vTE-cDWI with higher SNR compared to the acquired DWI, and dDLR increased the SNR more, as well as obtain ADC-maps and T1-maps with optimal TI for any arbitrary tissue. The clinical benefits of the method and results on volunteers are discussed.