Hella Code Visual Markers for Real-Time Tumor Tracking
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Solution Overview
Problem
Existing visual positioning technologies for tumor localization and tracking face challenges in achieving high precision and adaptability to flexible motion, while maintaining confidentiality and efficiency in radiotherapy settings.
Innovation Solution
A distributed multi-camera system employing visual position-aware markers with a Hella code-based encoding and recognition method, enabling real-time tumor positioning and tracking through spatial localization and full-view registration of mark features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-density self-recognition patterns are used for localization, then the recall rate for localization is improved, but the precision rate requires more stringent verification processes
Solution Approach 1:
The Hella code is divided into multiple self-recognizing units, each containing specific pattern elements. This segmentation allows the system to recognize tumor location through multiple independent units, improving both recall rate (more units increase detection probability) and precision rate (each unit provides verifiable position information) simultaneously.
Solution Approach 2:
The patent introduces a verification process as an intermediary between pattern recognition and final localization. This verification mechanism filters out false positives while maintaining high recognition speed, resolving the contradiction between precision requirements and processing efficiency.
2Adaptability or versatility
If mark features are distributed in multiple directions to adapt to flexible motion, then adaptability is improved, but synchronous registration in a single viewpoint becomes difficult
Solution Approach 1:
The Hella code design ensures that the same pattern structure can be recognized from multiple viewpoints and orientations. The self-recognizing units are arranged to provide universal recognition capability across different camera angles, enabling single-viewpoint registration while maintaining adaptability to flexible motion.
Solution Approach 2:
The patent employs asymmetric arrangement of self-recognizing units within the Hella code structure. This asymmetric design creates viewpoint-invariant recognition patterns that can be reliably detected from various angles, simplifying the registration process while maintaining motion adaptability.
3Reliability
If closed patterns such as characters and QR codes are used for self-recognition, then self-recognition capability is achieved, but confidentiality is compromised
Solution Approach 1:
The Hella code uses localized self-recognizing units with specific pattern characteristics that are distinct from conventional closed patterns. Each unit has unique local features that enable reliable recognition without using easily guessable or standardized patterns, thereby maintaining confidentiality while ensuring recognition reliability.
Data Source
AI summary
A distributed multi-camera real-time tumor positioning and tracking method based on a visual position-aware mark and tracking system thereof includes the steps: carrying out the coding of a high-density self-identification visual mark and obtaining a specific Hella code; detecting and identifying the Hella code; based on the identified Hella code, carrying out spatial positioning and full-view registration on the marked mark features, and applying the Hella code to tumor positioning and tracking. According to the method, high-precision sensing of the position of the patient is realized; by analyzing the medical image data, the position, posture, and anatomical structure information of the patient can be accurately determined, and accurate positioning and navigation are provided for accurate radiotherapy.