Keywords: AI/ML Image Reconstruction, AI/ML Image Reconstruction, DL Speed, AIR Recon DL
Motivation: DL Speed (DLS), a modified Sonic DL, is a new deep learning technology, reconstructing high-quality MRI images from under-sampled k-space data, providing minimal image degradation compared to standard methods.
Goal(s): To assess the performance of DLS-LAVA for breath-holding hepatobiliary phase (HBP) imaging in comparison with conventional LAVA.
Approach: In 20 liver MRI cases, DLS-LAVA and conventional LAVA were evaluated by two radiologists using qualitative and quantitative measures, including a liver-spleen intensity ratio (LSR).
Results: DLS-LAVA provided superior overall image quality, sharpness, and aliasing though graininess was slightly less favorable in some highly undersampled settings. DLS-LAVA achieved high-quality HBP images with shorter breath-holding times.
Impact: DLS-LAVA enables radiologists to obtain high-quality HBP images with reduced scan time, enhancing patient comfort and diagnostic precision compared to conventional LAVA. This advancement is especially valuable for patients with limited breath-holding capacity.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords