Webinar: Automated Segmentation and Design Workflows for Patient-Specific Surgical Guides
In this webinar, nTopology and Synopsys demonstrated a seamless patient-specific design workflow for a customized surgical guide that leverages AI-enabled patient image processing and design automation.
New technologies in the field of medical devices are making it possible to develop high-quality, fully customized 3D printed devices that make surgeries more efficient and improve patient outcomes. However, as demand for these highly customized devices grows, scaling the process to accommodate a higher throughput is limited by manual workflows that require significant labor and time. Two of the main time bottlenecks are segmentation – the process of converting 3D patient image data into surface models – and patient-specific design for additive manufacturing (DfAM) – the process of designing a 3D printed device based on the segmented patient anatomy.
In this webinar you will learn:
- How to efficiently convert 3D anatomical DICOM data into high-quality models using Synopsys Simpleware Software
- How nTopology can create fully-featured and conformal patient-specific solutions using scan data and reference landmarks
- How to automate the workflow and scale up to production levels
- Kerim Genc – Business Development Manager, Synopsys Simpleware Product Group
- Stephen Luke – Senior Applications Engineer, Synopsys Simpleware Product Group
- Christopher Cho – Staff Application Engineer | Additive Manufacturing & Medical Device Design, nTopology