Endoscopic Camera Calibration Using Lens Descriptors and Frame Imaging
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Solution Overview
Problem
Existing endoscopic camera systems with exchangeable, rotatable optics require costly and disruptive calibration methods that involve additional instrumentation and user intervention, such as using a rotary encoder or optical tracking, which are impractical and time-consuming, especially when changes in zoom or translation occur during surgical procedures.
Innovation Solution
A method for characterizing a rigid endoscope with a lens descriptor that allows automatic calibration of the endoscopic camera system by determining calibration parameters off-site, enabling seamless on-site operation without user intervention, and accommodating changes in zoom and translation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If rotary encoder or optical tracking systems are used for calibration, then calibration accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The system uses the endoscope's own imaging capability to perform calibration by capturing images of the Field Stop Mask, eliminating the need for external encoders or tracking systems. The calibration process is self-contained within the camera system itself.
Solution Approach 2:
The system creates a digital model (lens descriptor) of the endoscope's optical characteristics by capturing images of the Field Stop Mask, which serves as a reference copy for calibration purposes without requiring physical measurement instruments.
2Measurement precision
If rotary encoder or optical tracking systems are used for calibration, then calibration accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The calibration process requires no external instruments or complex user operations. The system automatically captures images of the Field Stop Mask and computes calibration parameters, making the process as simple as taking a picture.
Solution Approach 2:
The lens descriptor is pre-computed and stored in the camera system, so that when calibration is needed, the system can quickly retrieve and apply the stored parameters without requiring complex real-time measurements or user intervention.
3Measurement precision
If traditional calibration methods are used, then calibration accuracy is maintained, but productivity decreases due to time-consuming procedures
Solution Approach 1:
The lens descriptor containing calibration parameters is pre-computed and stored during manufacturing or initial setup. This allows the system to perform calibration instantly by retrieving stored parameters rather than performing time-consuming measurements during surgery.
Solution Approach 2:
The system replaces mechanical calibration procedures with automated image processing and computational algorithms, enabling rapid calibration through software rather than time-consuming physical adjustment and measurement processes.
4Measurement precision
If additional instrumentation is used for calibration, then calibration accuracy is improved, but loss of time increases due to setup and operation
Solution Approach 1:
The system extracts the calibration function from external instrumentation and integrates it into the camera system itself, using the existing imaging sensor and Field Stop Mask to perform calibration without requiring separate measurement devices.
Solution Approach 2:
The calibration process is entirely self-contained within the camera system, using its own imaging capability to capture the Field Stop Mask and compute parameters, eliminating the need for external instruments that would add setup and operation time.
5Adaptability or versatility
If exchangeable endoscopes are used, then adaptability is improved, but reliability of calibration deteriorates due to assembly variations
Solution Approach 1:
The system characterizes each endoscope individually by capturing its specific Field Stop Mask image and computing a unique lens descriptor. This local characterization ensures that calibration parameters are tailored to each specific endoscope-camerahad assembly, compensating for manufacturing variations.
Solution Approach 2:
The system adjusts calibration parameters dynamically based on the specific endoscope assembly by computing lens descriptors from captured images. This allows the system to adapt to parameter variations caused by different assemblies while maintaining reliable calibration.
Data Source
AI summary
A method for calibrating an endoscopic camera is described. The endoscopic camera includes an endoscope and a camera and the camera includes a camera head. The method includes receiving a lens descriptor associated with the endoscope, the lens descriptor including first calibration parameters indicating first characteristics of the endoscope independent of the endoscopic camera, with the endoscope installed in the endoscopic camera, acquiring an image frame using the endoscopic camera, detecting second characteristics of the image frame acquired using the endoscopic camera, calculating second calibration parameters using the lens descriptor and the second characteristics captured for the image frame, the second calibration parameters being different from the first calibration parameters, and at least one of storing and outputting the second calibration parameters to be used to operate the endoscopic camera.