AR Needle Positioning via Grayscale Marking Segmentation
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Solution Overview
Problem
The current augmented reality systems face challenges in maintaining needle positioning during medical procedures when the location code on the needle moves out of the camera's field of view.
Innovation Solution
An augmented reality system that includes a needle with distinct grayscale marking areas, a camera, an ultrasound generator, and a processor. The processor captures images of the needle's marking areas, uses linear regression algorithms for feature pose estimation, and adjusts the ultrasound field of view based on detected feature points to maintain positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single location code is used on the needle for positioning, then the positioning system is simple, but the positioning is terminated when the location code moves out of the camera's field of view
Solution Approach 1:
The needle is divided into multiple marking areas (first marking area with first grayscale color, second marking area with second grayscale color) instead of using a single location code. Each marking area can be independently detected, ensuring that positioning continues even when one marking area is out of the camera's field of view.
Solution Approach 2:
The solution transitions from a single-point location code to multiple distributed marking areas along the needle's length. This dimensional expansion from one to many provides redundancy, allowing the system to maintain positioning capability as long as at least two marking areas remain visible to the camera.
2Area of stationary object
If the camera field of view is limited, then the camera design is simple, but it is easy for the location code to move out of the detectable range during operation
Solution Approach 1:
By segmenting the single location code into multiple marking areas distributed along the needle, the system ensures that the limited camera field of view can still capture at least two marking areas even when the needle moves or bends, maintaining positioning reliability without requiring a larger camera field of view.
3Reliability
If multiple marking areas are detected to expand the field of view, then positioning continuity is improved, but the image processing complexity increases
Solution Approach 1:
The system uses the spatial relationship between marking areas with different grayscale colors to determine needle characteristics. By analyzing the local quality (grayscale color differences and positional relationships) of marking areas, the system can infer needle direction and bending without requiring complex global image processing.
Solution Approach 2:
The system changes the parameter of using grayscale color differences between marking areas as a key feature for detection. This parameter change simplifies the image processing by focusing on color/ intensity differences rather than complex shape recognition, making the algorithm more efficient while maintaining positioning continuity.
Data Source
AI summary
The augmented reality system includes a needle, a camera, an ultrasound generator, a memory, and a processor. The needle includes a location code, a first marking area, and a second marking area. The processor is used to perform following steps: capturing the location code, the first marking area, and the second marking area of the needle to perform positioning or a marking pose estimation by the camera; obtaining a feature points number according to the first marking area and the second marking area; obtaining a range prediction interval of the ultrasound field of view according to the feature points number of the needle; increasing or decreasing the range prediction interval according to the feature points number and a feature points number threshold; and when it is determined that the feature points number is greater than the feature points number threshold, the range prediction interval is reduced.