Foreign Object Extraction Planning From Surgical Imaging
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Solution Overview
Problem
Surgical procedures face complications due to undetected foreign objects, leading to improvised removal that can damage implant sites and prolong surgery, with existing methods lacking a systematic approach to address these objects during the procedure.
Innovation Solution
A computer-implemented method using an object-detection algorithm to identify foreign objects in medical images, determine their pose, and generate an extraction plan to safely remove them, integrating with a surgical system for automated guidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual improvised removal of foreign objects is performed during surgery, then the foreign object can be removed, but the surgical plan may be compromised and surgery duration is prolonged
Solution Approach 1:
The system performs preliminary detection of foreign objects using preoperative imaging (CT, MRI, X-ray) and object-detection algorithms before surgery begins. This allows the surgical plan to be adjusted in advance to account for foreign objects, eliminating the need for improvised removal during surgery and preventing disruptions to the surgical plan while avoiding time loss.
2Object-affected harmful factors
If foreign objects are detected and removed during surgery, then the surgical site can be cleared, but damage to implant receiving surfaces and sensitive structures may occur
Solution Approach 1:
The system generates a preoperative extraction plan that identifies safe removal paths and appropriate tools before surgery begins. This plan is integrated into the overall surgical plan, allowing the surgeon to follow a predetermined safe removal path that avoids damage to implant receiving surfaces and sensitive structures while ensuring complete foreign object removal.
Solution Approach 2:
The system uses preoperative imaging data and computational algorithms as an intermediary to plan the foreign object removal process. The object-detection algorithm identifies the foreign object's location and characteristics, and the system generates a removal plan that mediates between the need to remove the object and the need to protect surrounding tissues, providing a safe extraction path that avoids critical structures.
3Measurement precision
If automated object-detection algorithm is used to identify foreign objects, then detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system uses self-service by leveraging existing preoperative imaging data (CT, MRI, X-ray) that is already obtained for surgical planning purposes. The object-detection algorithm processes this existing data without requiring additional specialized imaging equipment or procedures, thereby improving foreign object detection accuracy while minimizing the increase in system complexity.
Data Source
AI summary
Computer-implemented methods, systems, software, and techniques involve using an object-detection algorithm to detect a foreign object in a medical image of a target anatomy. The foreign object is non-native to the target anatomy. The pose of the foreign object in the medical image and a surgical plan is associated with the medical image. An interaction between the foreign object and the surgical plan is determined. Based on the interaction, an extraction plan is generated for removing the foreign object from the target anatomy.