Anatomical Atlas Image Matching via Parameter-Driven Representation
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Solution Overview
Problem
Current methods for matching anatomical body structure images with general anatomical structure images from patient models are limited in adaptability and accuracy, particularly when dealing with different imaging modalities and pathological changes, as they fail to account for varying representation parameters and spatial distortions effectively.
Innovation Solution
A data processing method that determines a matching transformation by generating an atlas image set based on patient data and atlas data, using parameter sets to adjust representation data sets and spatial information, allowing for flexible matching across different imaging modalities and accounting for pathological changes through patho parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional image matching methods are used, then the matching process is simple, but the adaptability to different imaging modalities and pathological changes is poor
Solution Approach 1:
The patent applies parameter changes by adjusting representation parameters (such as image intensity, contrast, and spatial distortion characteristics) to account for different imaging modalities and pathological conditions. The system modifies atlas images based on patient-specific parameter sets that capture modality-specific characteristics and pathological variations, enabling accurate matching across diverse imaging types without requiring complex manual intervention.
2Measurement precision
If traditional image matching methods are used, then the processing time is short, but the accuracy for pathological changes and spatial distortions is insufficient
Solution Approach 1:
The patent implements preliminary action by pre-processing atlas images to generate multiple variants that account for different pathological changes and spatial distortions before the actual matching process. The system pre-computes representation parameters and spatial transformation models based on atlas data, so that when patient images are processed, the matching can proceed more efficiently using pre-prepared templates rather than performing complex real-time computations.
Solution Approach 2:
The system employs feedback mechanisms where patient image characteristics and matching results are used to iteratively refine the atlas image representation. The parameter sets are updated based on the degree of matching success, allowing the system to adapt to pathological changes and spatial distortions progressively, improving accuracy while managing processing time through iterative refinement rather than single-pass computation.
3Measurement precision
If detailed parameter adjustment is performed, then the matching accuracy improves, but the complexity of data processing increases
Solution Approach 1:
The patent applies segmentation by dividing the complex matching problem into separate modules: parameter set extraction, atlas image generation, and matching transformation. Each module handles specific aspects of the data processing independently - parameter extraction focuses on identifying modality-specific characteristics, atlas generation focuses on creating transformed templates, and matching focuses on computing the transformation. This segmentation reduces overall complexity by making each component more manageable and reusable.
Data Source
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AI summary
A data processing method for determining a matching transformation for matching a set of one or more images of an anatomical body structure of a patient, referred to as a patient image set, and a set of one or more images of a general anatomical structure, referred to as an atlas image set, wherein the general anatomical structure comprises a plurality of anatomical elements referred to as atlas elements, and each patient image is associated with one of a plurality of different parameter sets, wherein the parameter sets comprise one or more parameters which obtain when the patient images are generated, and the parameters influence representations of anatomical elements in the patient images, the method comprising the following steps performed by a computer: • acquiring atlas data, comprising the steps of - acquiring atlas spatial information which contains spatial information on the general anatomical structure, and - acquiring element representation information which describes a plurality of representation data sets (Table 3) which contain information on representations of the plurality of atlas elements in the atlas images to be determined, wherein the element representation information also describes a determination rule for determining respective representation data sets for respective atlas elements in accordance with different respective parameter sets; • acquiring patient data, comprising the sub-steps of - acquiring the patient image set, and - acquiring one or more of the plurality of parameter sets which are respectively associated with the one or more images of the patient image set; • determining, on the basis of the atlas data and the patient data, the set of atlas images which respectively represent at least a part of the general anatomical structure by using the spatial information on the general anatomical structure and particular representation data sets which are determined by applying the determination rule in accordance with the one or more associated parameter sets and particular atlas elements acquired and referred to as corresponding elements, which are to be matched to corresponding anatomical elements represented in the patient image; • determining the matching transformation (APT; APT1, APT2) which matches the atlas image set and the patient image set, by matching images associated with the same parameter set to each other.