Harnessing the enormous computational power of a Deep Convolutional Neural Network (DCNN), AiCE Deep Learning Reconstruction (DLR) is trained to differentiate signal from noise, so that the algorithm can suppress noise while enhancing signal. Because it is trained with advanced MBIR, it exhibits high spatial resolution. But unlike MBIR, AiCE DLR overcomes the challenges (image appearance and/or reconstruction speed) in clinical adoption.
AiCE DLR features:
Listen to Eliot Siegel, MD, FSIIM, FACR, Professor and Vice Chair Research Informatics, University of Maryland School of Medicine, Chief of Radiology and Nuclear Medicine, Veterans Affairs Maryland Healthcare System
Listen to Ewoud Smit, MD, PhD, from Radboud University Medical Center, Nijmegen, the Netherlands, explain how AiCE has won over even the most conservative radiologists in his department by offering them more diagnostic confidence.
Our partnership with NVIDIA® has allowed Canon Medical Systems to make significant advances in artificial intelligence (AI) and data-intensive deep learning techniques in the healthcare sector. The AiCE Server enables the processing of large volumes of medical data while simultaneously coordinating a variety of patient information.