Automated Perforator Vessel Positioning via 3D Image Reconstruction
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Solution Overview
Problem
The challenge in perforator flap surgery is the high variability and small caliber of perforator vessels, which are difficult to locate accurately, leading to high operation risks due to potential damage and lengthy manual image analysis by surgeons.
Innovation Solution
An automated method using three-dimensional image processing and machine learning to identify and position perforator vessels, involving dimension reduction, signal-to-noise ratio thresholding, and three-dimensional reconstruction to enhance and score candidate vessels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual image reading and positioning by surgeons is used, then positioning accuracy is achieved, but time consumption and energy expenditure are excessive
Solution Approach 1:
The system enables self-service by implementing automated algorithms that independently perform image analysis, perforator vessel identification, and positioning without requiring surgeon intervention. The computer automatically processes medical images, applies enhancement algorithms, and generates positioning results, freeing surgeons from this repetitive task while maintaining high positioning accuracy through validated computational methods.
Solution Approach 2:
The patent replaces the mechanical manual process of image reading and positioning with an automated computational system. Instead of surgeons manually analyzing images and marking positions, the system uses computer-based image processing algorithms, signal-to-noise ratio calculations, and automated reconstruction techniques to perform the same function, significantly reducing time consumption while preserving measurement precision.
2Productivity
If automated image processing is implemented, then processing speed is improved, but system complexity increases
Solution Approach 1:
The automated processing system is divided into distinct functional modules: image acquisition module, image enhancement module using signal-to-noise ratio analysis, perforator vessel identification module, three-dimensional reconstruction module, and positioning output module. Each module performs a specific function independently, making the complex system more manageable and easier to implement while achieving high processing speeds through parallel processing capabilities.
Solution Approach 2:
The system utilizes parameter changes in the image data, specifically employing signal-to-noise ratio thresholds and enhancement parameters to automatically distinguish perforator vessels from surrounding tissue. By dynamically adjusting these parameters based on image characteristics, the system achieves rapid processing without requiring overly complex algorithms, balancing speed and complexity effectively.
3Ease of manufacture
If traditional skin flap resection is used, then surgical procedure is simpler, but donor site damage is greater
Solution Approach 1:
The system performs preliminary action by automatically identifying and marking the precise locations of perforator vessels before the surgical procedure begins. This pre-operative positioning information allows surgeons to plan incisions and dissection paths that avoid damaging the perforators, thereby reducing donor site damage while maintaining surgical simplicity through guided rather than exploratory techniques.
Solution Approach 2:
The automated positioning system provides feedback to the surgical team by delivering precise location coordinates and visual markers of perforator vessels. This feedback enables surgeons to adjust their surgical approach in real-time, avoiding areas with critical vessels while maintaining the simplicity of the overall procedure through informed decision-making rather than complex manual exploration.
Data Source
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AI summary
The present invention relates to a method for automatically identifying and positioning a perforator vessel, a device, and a storage medium. The method comprises: according to a target perforator, determining a scanning range in a scanning direction, and extracting three-dimensional image data within the scanning range; performing dimension reduction processing on the three-dimensional image data to obtain layered segmented image data; taking the layered segmented image data as a minimum analysis unit, and screening for perforator vessel signal points by means of a signal-to-noise ratio dynamic threshold method; performing three-dimensional reconstruction on the perforator vessel by connecting the signal points in the three-dimensional image data, and screening for a candidate perforator vessel according to a signal-to-noise ratio total score after reconstruction; and determining a perforator vessel according to its relative position, its slope and depth to the epidermal layer and the deep muscle layer. The present invention can automatically and quickly position a perforator vessel.