Sila Kurugol1, Moti Freiman1, Onur Afacan1, Liran Domachevski2, Jeanette M. Perez-Rossello1, Michael J. Callahan1, and Simon K. Warfield1
1Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States, 2Nuclear Medicine, Rabin Medical Center, Petah-Tikva, Israel
Quantitative diffusion-weighted MRI (DW-MRI) has been
increasingly used for the detection and
characterization of abdominal abnormalities.
However, respiratory, cardiac and peristalsis motion deteriorates robustness
and reproducibility of parameter estimation in DW-MRI. Current solutions do not
entirely correct for motion and have disadvantages such as increased scan time.
In this work, we introduce a simultaneous image registration and model
estimation (SIR-ME) framework for motion-compensated parameter estimation. The
proposed method improved the goodness-of-fit by more than 50% and estimated
model parameters more precisely, resulting in better discrimination between
normal and diseased bowel loops, which will potentially impact clinical