Aquilion Exceed LB
Canon Medical Systems CorporationThe Aquilion Exceed LB is a whole-body multi-slice helical CT scanner that captures detailed cross-sectional images of the body, including the head. It incorporates AiCE, an AI-based noise reduction algorithm using deep convolutional neural networks, to improve image quality and reduce noise. This helps clinicians obtain clearer, more accurate diagnostic images for various body regions, including abdomen, pelvis, lung, cardiac, extremities, head, and inner ear.
Intended Use
This device is indicated to acquire and display cross-sectional volumes of the whole body, to include the head. The device provides volume sets used to perform specialized studies by trained and qualified physicians. AiCE is a noise reduction algorithm employing Deep Convolutional Neural Networks for abdomen, pelvis, lung, extremities, head and inner ear applications.
Technology
The device is a whole-body multi-slice helical CT scanner consisting of a gantry, couch, and a console used for data processing and display. It incorporates AiCE, an AI noise reduction algorithm using Deep Convolutional Neural Networks to improve image quality and reduce noise. It supports volume sets to perform specialized studies and includes features like Single Energy Metal Artifact Reduction (SEMAR), Dual Energy imaging, and advanced noise reduction processing methods.
Performance
Bench testing demonstrated substantial equivalence or improved performance in CT image quality metrics such as Contrast-to-Noise Ratios, CT Number Accuracy, Uniformity, Modulation Transfer Function, and Low Contrast Detectability. Phantom studies for Dual Energy imaging validated Electron Density and Effective Atomic Number accuracy. Clinical diagnostic images reviewed by a board-certified radiologist confirmed diagnostic image quality of AiCE reconstructions. Software validation and risk management were performed per FDA guidance.
Predicate Devices
No predicate devices specified
Device Timeline
- 1
Submission
6/14/2021
2 months - 2
FDA Approval
9/10/2021
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