Radiographic Image Processing for Surgical Tool Detection
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Solution Overview
Problem
Existing methods for detecting surgical tools in radiographic images after surgery are ineffective, as trained models often fail to detect tools due to the rarity of images with tools, leading to uncertainty about the discriminator's functionality.
Innovation Solution
A radiographic image processing device and method that generates a confirmation image by combining a radiographic image of a human body with a surgical tool image, using trained models to detect the tool's region, and adjusting parameters based on radiation absorptivity, scattering, and imaging conditions to ensure accurate detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a trained model is used to detect surgical tools in radiographic images, then detection capability is provided, but detection reliability deteriorates because images with surgical tools are extremely rare
Solution Approach 1:
The system performs preliminary action by generating a confirmation radiographic image that intentionally includes a surgical tool before actual detection occurs. This allows the discriminator to be pre-tested with known tool presence, ensuring it functions correctly when processing real post-surgery images where tools may be absent or difficult to detect.
Solution Approach 2:
The system creates a copy or synthetic representation of a radiographic image with a surgical tool (confirmation image) that can be used for verification purposes. This copied image with embedded tool information allows testing the discriminator without requiring rare real-world examples of retained surgical tools.
2Measurement precision
If surgical tools are not detected in radiographic images, then false negative results occur, but operator confidence in the discriminator's functionality deteriorates
Solution Approach 1:
The system implements feedback by providing the operator with a confirmation radiographic image that shows the detected surgical tool region. This visual feedback allows the operator to verify that the discriminator is functioning correctly and understand why a tool was or was not detected, thereby maintaining operator confidence even when tools are not detected in actual patient images.
Solution Approach 2:
The confirmation radiographic image acts as an intermediary between the discriminator and the operator. It translates the discriminator's detection results into a visual format that the operator can understand and verify, bridging the gap between automated detection and human confidence.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables operators to verify the correctness of surgical tool detection models by generating a confirmation image that highlights the surgical tool, improving detection accuracy and confidence in the discriminator's functionality.
Implementation Method 1
the processor may set the combination parameters according to at least one of radiation absorptivity of the surgical tool, a degree of scattering of radiation in the radiographic image
Implementation Method 2
the processor may set the combination parameters according to at least one of radiation absorptivity of the surgical tool, a degree of scattering of radiation in the radiographic image
Data Source
AI summary
A processor acquires a confirmation radiographic image including a surgical tool. In a case in which a radiographic image is input, the processor detects a region of the surgical tool from the confirmation radiographic image using a discriminator that detects the region of the surgical tool included in the radiographic image.