Meeting Banner
Abstract #0948

A Cartilage-Specific Loss Function Improves Image Reconstruction Performance in Multiple Tissues of Clinical Interest

Aniket Tolpadi1,2, Francesco Calivà1, Misung Han1, Emma Bahroos1, Peder Larson1, Sharmila Majumdar1, and Valentina Pedoia1
1Radiology and Biomedical Imaging, UCSF, San Francisco, CA, United States, 2Bioengineering, University of California, Berkeley, Berkeley, CA, United States


Most MRI image reconstruction algorithms are optimized for full-volume performance rather than specific tissues. Using a KIKI-Net style architecture and multi-component loss function in image space and k-space as baseline, we find a cartilage-specific loss function improves reconstruction performance at R=4 and R=8 in both cartilage and menisci. Thus, it may be possible to improve clinical utility of reconstruction pipelines across tissues of heightened clinical interest using a simple loss function weighting. Furthermore, full-volume standard reconstruction metrics worsened at R=4 and R=8 while tissue-specific metrics improved, calling into question whether these metrics are best for assessing reconstruction pipeline clinical utility.

This abstract and the presentation materials are available to members only; a login is required.

Join Here