Subject Pose Classification via Joint Coordinates
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Solution Overview
Problem
Accurate determination of a subject's pose is crucial for medical imaging and radiotherapy, but it can be challenging due to patient compliance issues and operator errors.
Innovation Solution
A medical instrument and method that automatically generate a subject pose label by analyzing joint location coordinates, using a predetermined logic module to determine orientations and poses such as head first, feet first, decubitus, supine, or prone, and calculating a torso aspect ratio to differentiate between poses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual pose recording is used, then operator flexibility is maintained, but measurement precision and reliability deteriorate due to operator errors and patient compliance issues
Solution Approach 1:
The system automatically detects and records pose information without requiring manual operator input. The pose detection device captures images and automatically processes them to determine pose labels, eliminating the need for operators to manually record pose data and reducing human error.
Solution Approach 2:
The patent replaces manual mechanical assessment of pose with an automated image processing system. The pose detection device uses computer vision algorithms to analyze images and automatically generate pose labels, substituting the manual mechanical process with an automated digital system.
2Reliability
If automated pose detection is implemented, then measurement precision improves, but device complexity increases
Solution Approach 1:
The system performs self-service by automatically capturing images, processing them through pose detection algorithms, and generating pose labels without requiring manual intervention. This automation improves reliability by eliminating human error while managing complexity through integrated software processing.
3Measurement precision
If detailed joint location analysis is performed, then measurement precision improves, but processing time increases
Solution Approach 1:
The system performs preliminary actions by capturing multiple images and pre-processing them before final pose determination. Joint location coordinates are calculated in advance from the captured images, allowing for more accurate pose classification without significantly increasing the critical processing time.
Solution Approach 2:
The pose detection system focuses on analyzing only the critical joint locations necessary for pose determination rather than processing the entire image in detail. This partial action approach maintains measurement precision for key pose indicators while reducing overall processing time by selectively analyzing only relevant regions.
Data Source
AI summary
Disclosed herein is a medical instrument (100, 300). Execution of the machine executable instructions causes a processor (106) to: receive (206) a set of joint location coordinates (128) for a subject (118) reposing on a subject support (120), receive (207) a body orientation (132) in response to inputting the set of joint location coordinates into a predetermined logic module (130), calculate (208) a torso aspect ratio (134) from set of joint location coordinates. If (210) the torso aspect ratio is greater than a predetermined threshold (136) then (212) the body pose of the subject is a decubitus pose. Execution of the machine executable instructions further cause the processor to assign (220) the body pose as being a supine pose if the subject is face up on the subject support or assign (222) the body pose as being a prone pose if the subject is face down on the subject support if the torso aspect ratio is less than or equal to the predetermined threshold. Execution of the machine executable instructions further cause the processor to generate (216) a subject pose label (142).