Spine Planning (2.0), Elements Spine Planning, Elements Planning Spine
Description
Spine Planning is intended for pre- and intraoperative planning of open and minimally invasive spinal procedures. It displays digital patient images (computed tomography (CT), Cone Beam CT, Magnetic resonance (MR), X-ray) and allows measurement and planning of spinal implants, such as screws and rods.
Detailed example
AI/ML algorithms are used in Spine Planning for detection of landmarks on 2D images for vertebrae labeling and measurement and vertebra detection on Digitally Reconstructed Radiograph (DRR) images of 3D datasets for atlas registration (labeling of the vertebra). The AI/ML algorithm is a Convolutional Neuronal Network (CNN) developed using a Supervised Learning approach. The algorithm was developed using a controlled internal process that defines activities from the inspection of input data to the training and verification of the algorithm.
AI / analytics pattern
Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Supports spine procedure planning.
Controls / human review
ATO: Not reported; PIA: Not published