GE HealthCare Technologies Inc. Launches CleaRecon DL, Introducing Ai-Based 3D Reconstruction to the Interventional Suite

Published: 2025-05-15 08:00:00 ET GEHC

Published on 05/15/2025 at 08:00, updated on 05/15/2025 at 09:20

GE HealthCare Technologies Inc. announced the launch of CleaRecon DL, technology powered by a deep-learning algorithm, to improve the quality of cone-beam computed tomography (CBCT) images. This artificial intelligence (AI)-driven solution is designed to remove streak artifacts caused by the pulsatile nature of blood flow in the arteries and changes in the distribution of contrast during CBCT acquisitions in liver, prostate, neuro, and endovascular aortic repair procedures. CleaRecon DL recently received U.S. FDA 510(k) clearance and CE mark and will be available for use on the Allia??

platform. CBCT is used in interventional suites to provide cross-sections imaging during procedures. However, the quality of CBCT reconstructed images may be diminished due to artifacts resulting from vessels' pulsatility, which can reduce image clarity and accuracy.

These limitations can impact the confidence in CBCT image interpretation and its adoption in routine clinical practice.2 Despite these challenges, CBCT remains crucial in interventional procedures for its ability to provide comprehensive visualization of anatomical structures and may enhance procedural accuracy. Deep learning is an AI technology that has become the machine learning technique for image processing and is trained to output data and perform specific tasks.3 It is based on population representative data collection and thorough tests with clinical domain experts. CleaRecon DL harnesses deep-learning algorithms designed to provide clearer and more accurate imaging, enabling healthcare professionals to make better-informed decisions and improve their patient care.

During clinical validation testing, a recent survey noted that in 98% of cases, CBCT images reconstructed with CleaRecon DL are clearer than conventional CBCT images. This technology was also shown to improve CBCT image interpretation confidence in 94% of cases.