Visualisation Device for Cervical Tissue Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing visualization devices struggle to accurately and consistently identify and track specific areas of cervical tissue during diagnosis and treatment, especially when the tissue is deformable due to mechanical or muscular movements, making it challenging to target precise areas for treatment while maintaining a stable camera perspective.
Innovation Solution
A visualization device that uses a camera and image processing system to detect and track reference structures, generate optical indicators, and apply transformations to maintain a stable reference image, allowing for precise localization of treatment areas regardless of camera or tissue movements, without requiring direct camera position detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If a stationary camera is used to capture images during tissue examination, then the camera position remains stable, but the tissue may move due to manipulation or muscular reactions causing misalignment of treatment areas
Solution Approach 1:
The system continuously captures images during the procedure and uses image processing to detect the current position of anatomical landmarks and treatment areas. Based on this feedback, transformation rules are dynamically calculated to map treatment areas from the reference image to the current live image, compensating for tissue movement and maintaining accurate localization throughout the procedure.
Solution Approach 2:
The system transitions from a static reference image to a dynamic tracking system that continuously updates the position of treatment areas. Transformation rules are recalculated in real-time based on detected changes in tissue position, allowing the system to adapt to movement while maintaining accurate treatment area identification.
2Ease of operation
If the camera moves during examination (e.g., head-mounted or shoulder-mounted), then the practitioner has hands-free operation, but the relative position between tissue and camera changes making treatment area tracking difficult
Solution Approach 1:
The system continuously monitors the live image feed from the moving camera and detects changes in the position of anatomical landmarks. Based on this feedback, transformation rules are dynamically adjusted to compensate for camera movement, ensuring that treatment areas remain accurately localized despite changes in camera position or orientation.
Solution Approach 2:
The system is designed to handle dynamic camera positions by continuously recalculating transformation rules based on the current camera orientation and position. This allows the practitioner to move freely while the system adapts to maintain accurate treatment area tracking in the live image feed.
3Measurement precision
If transformation rules are calculated based on anatomical landmarks, then treatment areas can be tracked independently of camera position, but the landmarks themselves may change due to tissue deformation or swelling
Solution Approach 1:
The system continuously updates the positions of anatomical landmarks throughout the procedure by detecting them in each live image. Transformation rules are dynamically recalculated based on the current positions of these landmarks, allowing the system to adapt to tissue deformation, swelling, or other changes that may occur during the procedure.
Solution Approach 2:
The system first captures a reference image with clearly visible anatomical landmarks before the procedure begins. This reference image serves as the initial basis for transformation rules, which are then continuously updated as the procedure progresses and tissue conditions change.
4Measurement precision
If multiple images are processed to track treatment areas, then accurate visualization is achieved, but the computational complexity and processing time increase
Solution Approach 1:
The image processing system divides the task into distinct stages: detecting anatomical landmarks, calculating transformation rules, applying transformations to locate treatment areas, and displaying results. This segmentation allows each component to be optimized independently and simplifies the overall processing pipeline.
Solution Approach 2:
The system performs preliminary detection of anatomical landmarks and calculation of transformation rules based on a reference image before the actual treatment begins. This preliminary processing establishes a foundation that reduces the computational burden during real-time tracking, as subsequent processing only requires detecting changes from the reference state.
Data Source
Figure 1~3
Figure 4
Figure 5~7
AI summary
The visualization device (1) according to the invention is used in particular for the diagnosis and monitoring of therapy in the treatment of biological tissue (2). It comprises a camera (4) and an image processing unit (5) connected thereto. The latter is configured to detect reference structures (7, 8) present on the tissue (2) in the images generated by the camera (4). It is further configured to detect and track optical indicators (9) generated by the examination, for example in a staining test. The optical indicators can be, for example, stained areas. By detecting and tracking the structures (7, 8), the image processing unit (5) determines perspective changes and generates corresponding transformation instructions.Using this, the image processing unit correctly positions the indicators (9), representations (10), and treatment points (14) in the reference image (0, 0', On), regardless of changes in the position of the camera (4), the patient, or tissue distortions. The optical indicators that mark tissue requiring treatment are thus correctly positioned and independent of patient or practitioner movements.