Wonderful dinner in London following #CMR2024, with tapas and live classical guitar, celebrating our collaboration with Drs. David Gross & Eric Anttila at MED Institute, and Dr. Craig Goergen and his group @CVIRLab @PurdueBME @dmyalcinkaya @KrannertHeart

Excellent #CMR2024 meeting in London (with surprisingly okay weather!) and a very good showing by our lab and @KrannertHeart with 6 oral presentations including an early-career award finalist in the translational category:

By converting the U-map to a dynamic quality control (dQC) metric, we refer the deep learning-generated segmentations that are identified as uncertain by our dQC metric for correction (clinician-in-the-loop A.I.). For more, see our MICCAI paper at arxiv.org/abs/2308.13488 (3/3):

After training a deep neural network for patch-level segmentation (see image below), we generate an uncertainty map (U-map) by exploiting the discrepancy between overlapping spatiotemporal (2D+time) patches in the dynamic image series (2/3):

A quick tour of our recent work on developing an efficient clinician-in-the-loop A.I. framework for dynamic contrast-enhanced MRI; led by @dmyalcinkaya & first published in #MICCAI2023 it is now extended to the multi-center SCMR Registry @ #CMR2024 rapid fire A.I. session (1/3):