Patient Positioning System Using Range Camera for MRI Alignment
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Solution Overview
Problem
Existing patient positioning systems for MRI require patients to be positioned near the MRI bore, exposing them to strong magnetic fields and high-intensity lasers, which can be uncomfortable and increase anxiety, and often result in inaccurate positioning of internal organs due to external reference points, leading to potential collisions and high setup costs.
Innovation Solution
A patient positioning device using a range camera to acquire 2D range images and determine a reference point on or inside the patient, allowing for accurate positioning outside the MRI room without lasers, reducing stress and the likelihood of collisions, and enabling precise internal organ targeting through 3D modeling and anatomical alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If lasers are used for patient positioning, then alignment accuracy is improved, but patient anxiety and discomfort increase due to high-intensity radiation
Solution Approach 1:
The patent replaces the optical laser alignment system with a camera-based vision system. Instead of using high-intensity lasers to project alignment patterns, the system uses a camera to capture images of anatomical landmarks and computationally determines alignment, thereby eliminating the harmful laser radiation while maintaining positioning accuracy
Solution Approach 2:
The patent creates a digital copy of the patient's anatomy by capturing images with the camera and generating a 3D anatomical model. This virtual model is then used for positioning and alignment calculations, replacing the need for direct laser projection on the patient's body
2Ease of operation
If external reference points are used for positioning, then ease of operation is improved, but manufacturing precision deteriorates due to inaccurate positioning of internal organs
Solution Approach 1:
The patent replaces manual external reference point selection with an automated image processing system. The camera captures images of anatomical landmarks, and computational algorithms automatically identify and locate internal organs, providing both ease of operation and high precision for internal structure positioning
Solution Approach 2:
The patent transitions from 2D external surface reference points to 3D internal anatomical landmark identification. By capturing images and generating 3D anatomical models, the system can precisely locate internal organs in three-dimensional space, improving positioning accuracy while maintaining operational simplicity
3Measurement precision
If patients are positioned inside the MRI room, then positioning accuracy is improved, but device complexity increases due to collision risks and magnetic field exposure
Solution Approach 1:
The patent performs all positioning and alignment calculations before the patient enters the MRI room. By pre-identifying anatomical landmarks and computing the 3D anatomical model in advance, the system eliminates the need for complex real-time positioning adjustments and safety protocols during the actual scanning process
Solution Approach 2:
The patent introduces a camera-based vision system as an intermediary between the patient and the MRI equipment. This intermediary system handles all positioning calculations externally, allowing the patient to be positioned accurately without being directly exposed to the MRI room's magnetic fields and collision risks
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
This solution allows for more accurate and comfortable patient positioning outside the MRI room, reducing anxiety and collision risks, improving patient throughput, and lowering setup costs by using 3D modeling to identify internal reference points and simulate the loading process.
Implementation Method 1
a range camera configured to acquire two-dimensional (2D) range images having pixel values corresponding to distances from the range camera
Data Source
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AI summary
A subject support (14) is configured to dock with a medical imaging device (50) with a fixed spatial relationship between the docked subject support and the medical imaging device. A patient positioning device includes a range camera (10) that acquires a two-dimensional (2D) range image of a human imaging subject (12) disposed on a subject support (14). The range image has pixel values corresponding to distances from the range camera. An electronic processor (16) is programmed to perform a positioning method to determine a reference point on or in the human subject in a frame of reference (FS) of the subject support from the 2D range image. This reference point is translated to a frame of reference (FD) of the imaging device based on a priori known spatial relationship of the medical imaging device and the docked subject support. Using 3D models, the loading process may be simulated.