3D CT Air Detection for Missed Free Intra-Abdominal Air
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current medical imaging technologies struggle to accurately and efficiently detect free intra-abdominal air, a critical condition requiring immediate surgical intervention, often leading to missed diagnoses due to its challenging visibility in CT scans and prioritization issues in emergency workflows.
Innovation Solution
A computer-implemented method and system using a trained function, such as a convolutional neural network, to analyze 3D medical imaging data, subdividing it into image patches to determine the presence of free intra-abdominal air, providing classification information or probability scores, and integrating with CT scanners for immediate notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual detection of free intra-abdominal air is performed by radiologists, then diagnostic accuracy can be maintained through expert judgment, but detection reliability deteriorates due to prioritization issues and time-critical workflow constraints causing missed diagnoses
Solution Approach 1:
The patent creates a virtual copy of the radiologist's detection capability through an automatic detection algorithm that analyzes CT images for free intra-abdominal air. This algorithmic copy operates independently of workflow prioritization issues, ensuring consistent detection across all cases regardless of reading order.
Solution Approach 2:
The patent introduces an automatic detection algorithm as an intermediary between the CT scanner and the radiologist. This intermediary pre-screens all images, flagging cases with free intra-abdominal air before human review, thereby ensuring no critical cases are missed due to prioritization delays.
2Productivity
If automatic detection algorithm is implemented, then detection productivity is improved through automated analysis, but device complexity increases due to integration requirements with CT scanners and workflow systems
Solution Approach 1:
The patent designs the automatic detection algorithm to be universally applicable across different CT scanner models and hospital workflows. By creating a platform-independent solution that interfaces with standard DICOM protocols, the system achieves high productivity without proportionally increasing complexity.
Solution Approach 2:
The detection algorithm operates autonomously, automatically analyzing CT images and generating detection results without requiring complex manual configuration or intervention. This self-service capability simplifies integration while maintaining high detection productivity.
3Loss of time
If CT scans are prioritized based on suspected critical conditions, then emergency response time is improved for obvious cases, but detection precision deteriorates as inconspicuous cases are skipped or delayed causing missed diagnoses
Solution Approach 1:
The patent performs preliminary automatic detection of free intra-abdominal air before radiologist review. This pre-screening identifies inconspicuous cases that would otherwise be missed during rapid prioritized reading, ensuring they receive appropriate attention without delaying obvious emergency cases.
Data Source
Figure 1
Figure 2
Figure 3(a)~3(d)
AI summary
The present invention relates to a method and system for the detection of free intra-abdominal air. In particular, the invention relates to a (e.g. computer-implemented) method for the detection of free intra-abdominal air, comprising: - receiving input data, said input data comprising a medical imaging data set of an abdominal region of a patient, e.g. via a first interface; applying a trained function, wherein the output data is generated, providing the output data e.g. via a second interface.