DICOM Image Data Linking for Registration Ambiguity
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Solution Overview
Problem
The DICOM standard inadequately addresses the separation and registration of medical image data volumes, particularly in cases where patient movement occurs during Functional MRI, and fails to explicitly define the separation of image data into volumes within a Series, leading to ambiguity and increased computational burden in determining proper registration transforms.
Innovation Solution
A data structure comprising a first image object, a second image object, and at least one linking object that establishes links between sets of image data, allowing for the creation of links from a source set of image data to a target set of image data, even when they belong to different series, and includes transformations to facilitate registration and navigation between image data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the DICOM standard is used to store and structure medical image data, then image data can be organized with attributes for patient identification, acquisition date, and modality, but the standard fails to explicitly define the separation of image data into volumes within a Series, leading to ambiguity in determining proper registration transforms
Solution Approach 1:
The patent segments the image data into distinct volumes within a Series by introducing volume-level attributes and explicit volume identification mechanisms. This allows the receiving application to clearly identify and separate individual volumes, eliminating ambiguity in registration transform determination while maintaining the overall DICOM structure.
Solution Approach 2:
The patent applies preliminary action by pre-defining volume separation and registration transform information within the DICOM data structure itself. The sending application provides explicit volume identification and transformation attributes before the data is received, so that the receiving application does not need to perform complex analysis to determine volume boundaries or registration transforms.
2Adaptability or versatility
If the DICOM standard provides Frame of Reference Information Entities to spatially relate multiple Series, then spatial relationships can be established, but considerable guesswork is required by the receiving application to determine what images constitute a set, a set of single images or a volume
Solution Approach 1:
The patent segments the ambiguity resolution by introducing explicit volume-level attributes and identification mechanisms within the DICOM standard. This allows the receiving application to automatically and easily determine what images constitute a volume without requiring guesswork, while maintaining the Frame of Reference capabilities for spatial relationship establishment.
Solution Approach 2:
The patent introduces volume identification attributes and transformation information as intermediary elements between the Frame of Reference Information Entities and the image data. These intermediary structures provide clear definitions that mediate between the high-level spatial relationship capabilities and the low-level image composition determination, eliminating the need for guesswork.
3Measurement precision
If multi-frame CT, MRI and PET Objects were introduced in 2005 to characterise volumes by explicitly defined dimensions, then volume characterisation improved, but the structure is still insufficient to identify when an object changes orientation within a multi-frame object
Solution Approach 1:
The patent applies dynamics by introducing dynamic orientation tracking capabilities within the volume characterisation framework. The enhanced DICOM structure includes attributes that can detect and record changes in object orientation within multi-frame objects, allowing the system to adapt to dynamic repositioning while maintaining precise volume characterisation.
Solution Approach 2:
The patent applies preliminary action by pre-including orientation information and transformation attributes within the volume characterisation data structure. This preliminary inclusion of orientation data allows the receiving application to immediately identify orientation changes without requiring additional analysis or guesswork, while maintaining the precision of volume characterisation.
Data Source
AI summary
A data structure stored on a non-transitory medium includes: a first image object and a second image object, each comprising image data and series data corresponding to a series to which the image data belongs; and at least one linking object which is an instance of a linking class which is configured to provide for instantiation of linking objects which each define a link from at least one source to a target, the source corresponding to at least one of a series and a set of image data and the target corresponding solely to a series. The linking object includes target data corresponding to a target series which is other than the series to which the first and second sets of image data belong and source data corresponding to the first image data.