DICOM Series Splitting via Rules-Based Frameset Engine
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Solution Overview
Problem
Conventional methods for sorting and reordering medical image studies are inefficient, prone to human error, and do not conform to individual physician or facility preferences, as they rely on manual sorting and do not effectively group clinically relevant images into framesets.
Innovation Solution
A user-configurable rules-based engine for DICOM viewing applications that automatically splits DICOM medical image series into framesets by predefined DICOM tags, allowing users to customize the grouping of images based on specific criteria such as anatomical views, laterality, and frame of reference, ensuring that only images with identical tags are included in a single frameset.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual sorting and reordering of medical image studies is performed by a quality control technologist, then the images can be arranged in a predetermined format, but the method is inefficient, cumbersome, and subject to human error
Solution Approach 1:
The system enables self-service automation where the computer system automatically sorts and reorders DICOM image series into framesets based on predefined criteria without requiring manual intervention by quality control technologists. The automated processing eliminates human error while maintaining high efficiency through algorithmic sorting based on DICOM tags and user-defined parameters.
2Adaptability or versatility
If manual sorting methods are used to arrange image studies, then a predetermined format can be achieved, but the method does not conform to individual physician or facility preferences
Solution Approach 1:
The system implements dynamic adaptability through user-configurable parameters that allow physicians and facilities to customize sorting criteria according to their specific preferences. The sorting algorithm can be dynamically adjusted based on selected DICOM tags, anatomical views, laterality, and other relevant parameters, enabling the system to adapt to different user requirements without requiring complex manual configuration.
3Productivity
If automated splitting of DICOM image series into framesets is implemented based on predefined DICOM tags, then efficient and accurate sorting is achieved, but the system requires user configuration of tags and criteria
Solution Approach 1:
The system performs preliminary action by pre-defining common DICOM tags and sorting criteria that are frequently used in medical imaging. Users can select from pre-configured tag options and templates, which reduces the complexity of initial setup while still allowing for customized configuration when needed. This approach enables efficient automated sorting without requiring users to manually configure every parameter from scratch.
Data Source
AI summary
Systems and methods are described for splitting DICOM medical image series into framesets. In one implementation, a method of splitting a DICOM medical image series into framesets includes determining that a first DICOM image object of the DICOM medical image series is the first DICOM object of the medical image series and creating a first frame set including the first DICOM image object in response to determining that the first DICOM image object is the first DICOM object of the medical image series. In subsequent steps, the method may include determining that a second DICOM image object of the DICOM medical image series does not have more than one image frame; and determining whether a first predefined DICOM tag of interest of the second DICOM image object matches a first DICOM tag of interest of a first image of the first frameset.