X-ray Image Metal Detection Using Trained Model

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing medical imaging systems struggle to accurately distinguish metal objects from human tissues in X-ray images, leading to difficulties in medical diagnoses.

Innovation Solution

A system and method for processing X-ray images using a trained metal detection model, which determines a metal image by identifying metal objects within the X-ray image, and optionally adjusts radiation doses based on image analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional image processing methods are used to analyze X-ray images, then the system complexity remains low, but the ability to distinguish metal objects from human tissues is insufficient

Engineering Contradiction:

Improvemetal detection accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent introduces a trained metal detection model as an intermediary component between the X-ray image input and the diagnostic output. This model acts as a specialized mediator that processes the image data and extracts metal object information, thereby improving detection accuracy without requiring complete redesign of the entire imaging system.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces traditional mechanical/image processing methods with an intelligent metal detection model based on machine learning. This substitution enables the system to automatically identify and distinguish metal objects from human tissues with higher precision, overcoming the limitations of conventional processing algorithms.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If higher radiation doses are used to improve image quality, then the image quality improves, but the radiation exposure to patients increases

Engineering Contradiction:

Improveimage qualityVSAvoidradiation exposure

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent implements a feedback mechanism where the metal detection model analyzes the X-ray image and provides information about metal objects present. This feedback allows the system to adjust imaging parameters and radiation doses based on the detected metal objects, optimizing image quality while minimizing unnecessary radiation exposure to patients.

Inventive Principle:

Principle #23Feedback

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

The system effectively identifies metal objects in X-ray images, improving diagnostic accuracy and potentially reducing radiation exposure by optimizing imaging parameters.

Implementation Method 1

The X-ray imaging device (e.g., a medical X-ray diagnostic device, a medical X-ray treatment device, a computed tomography (CT) device, etc.) may scan an object (e.g., a tissue, a bone, etc.) using radiation rays and generate one or more images relating to the object.

Methodology Applied

Scientific EffectX-ray radiation: X-Ray

Data Source

PatentUS20250166205A1Systems and methods for processing x-ray images

Publication Date: 2025.05.22 SHANGHAI UNITED IMAGING HEALTHCARE

AI summary

The present disclosure is related to systems and methods for processing X-ray images. A method for processing an X-ray image may include obtaining an X-ray image; and determining a metal image based on the X-ray image by using a trained metal detection model. The metal image includes information of a metal object in the X-ray image.