Object Orientation Recognition System for Medical Imaging
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Solution Overview
Problem
Manual entry of patient orientation in medical imaging systems can lead to incorrect orientation information, increasing diagnosis time and potentially resulting in incorrect diagnoses due to operator error.
Innovation Solution
An object orientation recognition system (OORS) with feature recognition devices and a module (OORM) that automatically determines the patient's orientation by comparing user input with data from cameras or x-ray detectors, generating images with orientation indicia based on the comparison.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual entry of patient orientation is used, then operator control is maintained, but orientation accuracy deteriorates due to human error
Solution Approach 1:
The system automatically determines patient orientation using image processing and feature recognition algorithms that analyze anatomical landmarks in the imaging data, eliminating the need for manual operator input and thereby preventing human error while maintaining operational simplicity
Solution Approach 2:
The manual mechanical process of orientation entry is replaced with an automated computational system that uses image processing algorithms to detect anatomical features and automatically determine correct orientation, substituting human judgment with algorithmic analysis
2Reliability
If automatic orientation determination is implemented, then orientation accuracy improves, but device complexity increases
Solution Approach 1:
The feature recognition system leverages existing imaging data already captured during the medical imaging process, making the orientation determination function utilize existing infrastructure and data streams rather than requiring separate dedicated hardware systems
Solution Approach 2:
The system introduces an intermediary processing layer that automatically interprets imaging data to determine orientation, acting as a bridge between the raw imaging data and the final oriented output, thereby managing complexity through modular software architecture
3Productivity
If manual orientation entry is used, then system simplicity is maintained, but diagnosis time increases due to verification needs
Solution Approach 1:
The system performs preliminary automatic orientation determination before the diagnostic process begins, ensuring that orientation is correctly established in advance, which eliminates the need for physicians to spend time verifying or correcting orientation during diagnosis
Solution Approach 2:
The system provides feedback by comparing the automatically determined orientation with expected anatomical relationships, and can alert operators to potential errors, creating a self-verifying system that reduces the need for manual verification during diagnosis
Data Source
AI summary
A method for determining a subject's orientation includes receiving, at an imaging system, an input that indicates an orientation of a subject being imaged, automatically determining the orientation of the subject using a feature recognition system, comparing the received input to the automatically determined orientation, and generating an image, the image including orientation indicia based on the comparison. An object orientation recognition system and an imaging system are also described herein.