This single-centre retrospective study aimed to evaluate a deep learning (DL) algorithm for detecting vessel steno-occlusions in peripheral arterial disease patients (PAD). The authors’ findings suggest that the proposed DL model is promising and an effective tool to assist in the detection of arterial steno-occlusions in PAD patients. Key points: This study focused on the application of DL for arterial steno-occlusion detection in lower extremities on MRA. A previously developed DL model was tested for accuracy and inter-reader agreement. While the model showed promising results, it does not yet replace human expertise in detecting arterial steno-occlusion on MRA. Article: Detection of femoropopliteal arterial steno-occlusion at MR angiography: initial experience with artificial intelligence Authors: Tri-Thien Nguyen, Lukas Folle & Thomas Bayer
Impact of deep learning reconstruction on radiation dose reduction and cancer risk in CT examinations
Deep‑learning reconstruction (DLR) shifts CT image formation from a hardware‑limited process to a data‑driven one. In our real‑world cohort of >10,000 body scans, we observed a
28. April 2025
