What To Know
- We have interacted with the Simpleware Product Group at Synopsys for solutions to this challenge and are excited with the development of their automated ML-powered tools for the rapid segmentation of clinical images which aligns closely with our own innovation needs.
- In the case of medical device design and pre-surgical planning, segmentation of the human anatomy is one of the key bottlenecks to getting on to more meaningful analysis and product innovation.
Simpleware AS Ortho
Highlights:
- Automated 3D image segmentation module powered by Artificial Intelligence (AI) technology using Machine Learning (ML) algorithms
- Time and cost-saving, scalable solution for medical device R&D, pre-surgical planning, and in silico clinical trials
- Based on hundreds of hours of algorithm training from medical datasets with outputs checked by clinical professionals, ensuring reliable and consistent results
- Includes additional capabilities for automated landmarking of segmented image data
Industry Challenges
Segmentation of 3D image data from sources like MRI and CT is typically very time-consuming, with those working on the data having to take the time to extract regions of interest form data when working on models. In the case of medical device design and pre-surgical planning, segmentation of the human anatomy is one of the key bottlenecks to getting on to more meaningful analysis and product innovation.
Synopsys, Inc. are tackling this challenge with the launch of Simpleware AS Ortho (Auto Segmenter for Orthopedics), a new Simpleware ScanIP software module for automated segmentation of medical images. Simpleware AS Ortho is powered by Artificial Intelligence (AI) technology using Machine Learning (ML) algorithms.
Embedded in the Simpleware ScanIP software platform and building on its established segmentation capabilities, the new module significantly reduces traditional bottlenecks around manual segmentation of hips and knees. With Simpleware AS Ortho, users will see a 20 to 50 times faster rate of segmentation, meaning that previously tedious work is reduced or eliminated altogether to free up engineering time and resources for analysis and innovation.
Why It Matters
According to the journal Orthopedic Surgery, total knee arthroplasties (TKAs) in the USA will grow by 484%, from 719,000 in 2015 to 3.48 million by 2030, while total hip arthroplasties (THAs) will grow by 172%, from 332,000 to 572,000 in the same period. The Simpleware AS Ortho, together with Simpleware ScanIP, helps reduce the difficulty of meeting this demand, as described below by Johann Henckel MD, Orthopaedic Surgeon, Royal National Orthopaedic Hospital, UK.
“Image segmentation of MRI and CT scans presents a significant challenge for our surgical and engineering multidisciplinary teams. We have interacted with the Simpleware Product Group at Synopsys for solutions to this challenge and are excited with the development of their automated ML-powered tools for the rapid segmentation of clinical images which aligns closely with our own innovation needs. What is currently a laborious process that occupies significant engineering resources and time, can now be completed quickly, accurately and with less variability, promising a scalable solution for generating high-fidelity patient-specific models, surgical tools and bespoke implants.”
