Ultrasound Foreign Body Detection Algorithm
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Solution Overview
Problem
Current neurosurgical practices face challenges in detecting and localizing foreign body objects, such as cotton balls, during and after surgery, due to their similarity in appearance to brain tissue, leading to potential retention and complications.
Innovation Solution
The development of a fully automated foreign body object tracking algorithm using ultrasound imaging and a custom convolutional neural network, which achieves 99% accuracy in detecting and localizing retained cotton balls by leveraging their distinct acoustic properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If cotton balls are used to clear the view during neurosurgery, then the surgical field visibility is improved, but the risk of foreign body retention increases
Solution Approach 1:
The patent replaces manual visual inspection with an automated ultrasound-based detection system. The mechanical/visual method of monitoring cotton ball placement is substituted with acoustic imaging technology that automatically identifies and localizes foreign bodies in real-time during surgery, eliminating reliance on surgeon visual assessment
Solution Approach 2:
The patent introduces ultrasound imaging as an intermediary detection mechanism between the cotton balls and the surgeon's awareness. The ultrasound system acts as a mediator that translates the acoustic properties of cotton balls into visualizable data, allowing indirect detection of foreign bodies that are otherwise difficult to distinguish from brain tissue
2Device complexity
If manual inspection methods are used to detect foreign bodies, then the system complexity is low, but the detection precision deteriorates
Solution Approach 1:
The patent changes the detection parameter from visual appearance to acoustic properties. By measuring the acoustic impedance and sound wave reflection characteristics of cotton balls, the system achieves superior detection precision. This parameter transformation allows differentiation of cotton balls from brain tissue based on their distinct acoustic signatures rather than visual similarity
Solution Approach 2:
The patent transitions from two-dimensional visual inspection to three-dimensional acoustic imaging. Ultrasound technology provides depth information and spatial localization that manual visual inspection cannot achieve, enabling precise identification of foreign bodies' position, size, and shape within the surgical field
3Measurement precision
If automated detection algorithms are implemented, then the detection accuracy is improved, but the processing time increases
Solution Approach 1:
The patent performs preliminary processing of ultrasound images during acquisition and uses pre-trained deep learning models. By preparing the detection system in advance with trained algorithms and processing images as they are acquired rather than in batches, the system achieves high detection accuracy without significant time loss during the surgical procedure
Solution Approach 2:
The patent uses digital copies of ultrasound images for algorithmic analysis rather than manipulating the physical imaging process. The deep learning algorithms process digital representations of the acoustic data, enabling rapid and accurate foreign body detection without requiring additional physical measurements or repeated imaging
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 algorithm effectively prevents accidental foreign body retention by rapidly and accurately identifying cotton balls in ultrasound images, demonstrating its clinical relevance and potential to improve patient outcomes and reduce surgical errors.
Implementation Method 1
the different acoustic properties of cotton and brain tissue result in two discernible materials
Data Source
AI summary
Systems and methods for detection and localization of a foreign body object in a region are provided. In embodiments, a system can a processor and one or more computer-readable storage media storing instructions which, when executed on the processor, cause the processor to perform a method for forming a trained model using a plurality of training images and a plurality of training boundary data sets. The systems and methods further apply the trained model to process an image and generate a boundary data set. In embodiments, the image can be an ultrasound image, and the boundary data set can correspond to a bounding box enclosing the foreign body object.