Chest CT Segmentation - Case study
The challenge
- An industry-leading medical device company required the capability to automatically generate an accurate 3D model of complex patient-specific anatomies
- The anatomical model was needed for planning challenging surgical navigation procedures
- The pre-existing solution was slow and not robust, requiring extensive and time-consuming manual editing by the interventionist
Our approach
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The RSIP Vision team leveraged its deep-learning based 3D CT auto-segmentation technology to deliver a customized, fast, robust, production quality solution
The outcome
- Our core module has been integrated into our clients platform and is in clinical use
- Used in 1000s of cases in hospitals worldwide
- >99% segmentation success rate
- 1mm-level segmentation resolution
- 30 seconds running time on full-sized chest CT scan
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