Medical Reporting Apparatus Frame Selection
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Solution Overview
Problem
In medical procedures like angiography, generating comprehensive reports is challenging due to the time-consuming process of extracting and editing multimedia content from imaging equipment, leading to incomplete reports with redundant information.
Innovation Solution
An apparatus and method for computer-aided medical report provision that processes frames from medical imaging devices, selects relevant frames based on contextual information such as orientation, procedure status, and contrast agent quality, to generate a concise multimedia or documentary report by omitting redundant frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If manual extraction and editing of images and videos from imaging equipment is performed, then comprehensive multimedia content can be included in reports, but the process becomes extremely time-consuming and labour-intensive
Solution Approach 1:
The system enables automatic self-service reporting by having the imaging equipment automatically generate and structure multimedia reports using embedded sensors, processors, and algorithms that autonomously select, annotate, and organize images and videos without requiring manual extraction or editing by medical professionals
Solution Approach 2:
The system performs preliminary actions by automatically capturing contextual information (orientation, procedure status, event signals) and pre-organizing multimedia content during the medical procedure itself, so that report generation is already substantially complete before the procedure ends, eliminating post-procedure manual work
2Loss of information
If all frames from medical imaging devices are included in reports, then complete procedural documentation is achieved, but data size becomes unmanageably large with redundant information
Solution Approach 1:
The system extracts only the essential and non-redundant frames from the complete frame sequence by using processors to analyze contextual information and identify frames that represent meaningful procedural events, removing duplicate or unnecessary frames while preserving complete procedural documentation
Solution Approach 2:
The system applies different quality levels to different frames based on their clinical significance, maintaining high detail for frames capturing important procedural events while reducing or omitting less critical frames, thereby optimizing data size while preserving essential information
3Measurement precision
If comprehensive contextual information from multiple equipment inputs is collected, then frame selection accuracy is improved, but system complexity increases
Solution Approach 1:
The system achieves multi-functionality by designing a universal processing framework that can handle multiple types of contextual information (orientation data, procedure status, event signals) through a single integrated processor that performs all analysis and frame selection functions regardless of the specific input source or procedure type
Data Source
AI summary
During a medical intervention such as an angiography, the X-ray examination equipment (such as that mounted on a C-arm) produces a very large number of imaging frames of the intervention, as it progresses. This information contains frame sequences which can be effectively used to improve a medical report of the intervention. The sequence will contain sequences which contain similar clinical information though, and these frames may be considered to be redundant and not useful for inclusion in the medical report. The aspects detailed herein enable a selection of non-redundant sequences and/or frames, based on contextual information, obtained from the sequence of images, and/or other medical equipment, during an intervention. In this way, the redundancy inherent in the original frame sequence can be removed, leaving a set of prepared candidate sequences for insertion into a multimedia or documentary medical report.