1 citations · 1 across the 3 of their papers we have counts for
3 papers
q-bio.QM2024
Fast Whole-Brain MR Multi-Parametric Mapping with Scan-Specific Self-Supervised Networks
Amir Heydari, Abbas Ahmadi, Tae Hyung Kim +1
Quantification of tissue parameters using MRI is emerging as a powerful tool in clinical diagnosis and research studies. The need for multiple long scans with different acquisition…
physics.med-ph2023
Blip-Up Blip-Down Circular EPI (BUDA-cEPI) for Distortion-Free dMRI with Rapid Unrolled Deep Learning Reconstruction
Uten Yarach, Itthi Chatnuntawech, Congyu Liao +9
Purpose: We implemented the blip-up, blip-down circular echo planar imaging (BUDA-cEPI) sequence with readout and phase partial Fourier to reduced off-resonance effect and T2* blur…
eess.IV2021★ 1 cited
Accurate parameter estimation using scan-specific unsupervised deep learning for relaxometry and MR fingerprinting
Mengze Gao, Huihui Ye, Tae Hyung Kim +3
We propose an unsupervised convolutional neural network (CNN) for relaxation parameter estimation. This network incorporates signal relaxation and Bloch simulations while taking ad…