Robotic Cranial Registration Using 3D Surface Imaging
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Solution Overview
Problem
Image-guided surgery for glioma removal faces challenges due to brain shift phenomena and inaccuracies in neuronavigation systems, making preoperative images unreliable during surgical procedures.
Innovation Solution
A system utilizing a movable elliptical mask attached to a robotic arm for surface imaging, combined with machine vision and infrared sensors, to create and register 3D models of the cranium, reducing the need for manual registration and enhancing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If preoperative images are used for image-guided surgery, then surgical planning can be completed beforehand, but the images become unreliable during surgery due to brain shift phenomenon
Solution Approach 1:
The system performs preliminary actions by acquiring preoperative modality scans (CT, MRI, PET, SPECT) and creating a 3D image source before surgery. This allows surgical planning to be completed beforehand while establishing a baseline for later comparison with intraoperative surface imaging data, addressing both the time efficiency of preplanning and the reliability issue through subsequent updates.
Solution Approach 2:
The system implements feedback by continuously comparing preoperative images with intraoperatively acquired surface imaging data. The neuronavigation system uses this feedback to update the 3D model during surgery, compensating for brain shift phenomenon and maintaining image accuracy throughout the procedure.
2Measurement precision
If manual tracer placement is used for re-registration of intraoperative images, then updated anatomical views can be obtained, but the process requires significant manual effort and time
Solution Approach 1:
The system replaces the manual mechanical process of tracer placement with an automated optical scanning system. A robotic arm equipped with cameras and sensors automatically captures surface imaging data by moving around the patient's head, eliminating the need for manual tracer placement while maintaining or improving registration accuracy through sophisticated image processing algorithms.
Solution Approach 2:
The system enables self-service by allowing the imaging system to automatically capture, process, and register surface data without requiring manual intervention. The robotic arm autonomously navigates around the patient's head, captures images from multiple angles, and the system automatically performs the registration process, significantly reducing manual effort and time requirements.
3Extent of automation
If a robotic arm with machine vision system is used for surface imaging, then automated registration can be achieved, but the device complexity increases
Solution Approach 1:
The robotic arm system is designed with multi-functionality, serving both as a positioning mechanism and an imaging platform. By integrating cameras, infrared sensors, and other detection devices onto the robotic arm, the system achieves automated registration while consolidating multiple functions into a single device, thereby managing complexity rather than increasing it proportionally.
Solution Approach 2:
The system merges the robotic arm positioning system with the machine vision imaging system into an integrated platform. This combination allows the same mechanical structure to perform both precise positioning and data acquisition functions, reducing the need for separate systems and managing overall device complexity while achieving high automation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides accurate and automated image registration, allowing for precise cranial surgical navigation by continuously monitoring and adjusting to anatomical changes, thus improving surgical precision.
Implementation Method 1
The surface imaging data are used to create a 3D image target. The machine vision system utilizes at least one imaging sensor, at least one infrared sensor, or a combination thereof.
Data Source
AI summary
The disclosed systems, methods, and techniques perform an imaging registration and a cranial surgical procedure navigation. In one aspect, the systems, methods, and techniques use modality scans of the cranium of the patient, which are obtained preoperatively, to create a 3D image source. Then, using a machine vision system embedded in or on a movable elliptical mask attached to a robotic arm, the systems, methods, and techniques obtain surface imaging data of a face or a portion of the cranium of the patient while the patient is lying in a supine position atop an operating table. The surface imaging data are used to create a 3D image target. The 3D image target then is registered to the 3D image source to complete the imaging registration. Once the imaging registration is complete, a surgeon can perform an image-guided surgery of the cranium of the patient.