Medical Imaging Probe Guidance via Position Feedback
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Solution Overview
Problem
In medical imaging procedures, inexperienced users face challenges in accurately navigating a medical imaging probe to obtain desired scan planes of anatomical structures, leading to potential improper diagnosis due to difficulties in finding target views.
Innovation Solution
A method that utilizes image data and position data from a probe's position sensor to guide users by outputting instructions on how to navigate the probe to desired scan planes, incorporating machine learning algorithms and anatomical structure models to enhance accuracy and assist in identifying target anatomical structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional frameworks are used for image analysis, then a broad range of applications can be covered, but the system cannot provide real-time guidance to users on probe navigation
Solution Approach 1:
The system continuously receives image data and position data from the probe, processes this information through machine learning algorithms, and provides real-time feedback instructions to guide the user in navigating the probe to obtain desired scan planes. This closed-loop feedback mechanism enables dynamic user guidance while maintaining broad application coverage through the versatile machine learning framework.
2Measurement precision
If machine learning algorithms are implemented for automatic detection, then detection accuracy improves, but system complexity increases
Solution Approach 1:
The patent introduces a machine learning-based detection framework as an intermediary between the raw image data and the user. This framework automatically detects scan planes and anatomical structures, providing accurate measurements while shielding the user from the underlying system complexity. The framework acts as a smart mediator that translates complex image analysis into simple, actionable guidance instructions.
3Ease of operation
If real-time guidance is provided during imaging procedures, then ease of operation improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-training machine learning models on extensive datasets of medical images and anatomical structures before actual imaging procedures. This preliminary training enables the system to rapidly process real-time image data during procedures without requiring extensive computational resources or time, as the heavy lifting of pattern recognition has already been accomplished during the pre-training phase.
Data Source
AI summary
Various methods and systems are provided for automatically detecting scan planes of anatomical structures and providing guidance for obtaining target views during an imaging procedure. As one example, a method includes outputting to a user, instructions for navigating a medical imaging probe from a current scan position to a next scan position for obtaining a desired scan plane of a target anatomical structure based on received image data of the target anatomical structure and position data, the position data obtained from a position sensor on the probe, during receiving the image data.