Synopsys, Inc. announced the release of a major update to Simpleware ScanIP software, which extends its capabilities for segmenting anatomical regions through a new module, Simpleware AS Ortho (Auto Segmenter for Orthopedics). This new product offering is a machine learning (ML)-based auto segmentation module that builds on Synopsys' ScanIP software, a comprehensive solution for 3D image processing and segmenting images generated by computed tomography (CT) or magnetic resonance imaging (MRI) scanners.
The newly launched ML-based Simpleware AS Ortho is a module specifically designed for segmentation needs in the hips and knees. When applying this automated option with Synopsys' ScanIP software to run their analysis, users will easily see a 20 to 50 times faster rate of segmentation for clinical images. This revolutionary technology is fully scalable, and while helping to achieve more consistency and increased reliability in biomechanical compatibility, it can also dramatically streamline the workflow process in both pre-surgical planning and medical device design. Users will thus achieve significant cost-savings in the product development cycle.
Based on research by the journal Orthopedic Surgery, total knee arthroplasties (TKAs) in the USA will grow from 719,000 in 2015 to 3.48 million by 2030, while total hip arthroplasties (THAs) will almost double from 332,000 to 572,000 in the same period. This new ML-based product offering is an exciting new step for Synopsys' role in these fast-growing healthcare medical markets.
Availability and resources
Synopsys' Simpleware AS Ortho (Auto Segmenter for Orthopedics) is launching in March 2020 as a Simpleware ScanIP software add-on module for hips and knees. In time, further modules will be added to provide automated segmentation options for other anatomical regions. For users wanting any customization, or workflows applied to different anatomies, Synopsys' Simpleware Custom Modeler option is also available as a fully tailored and automated solution.
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