Tomographic Image Resolution Enhancement for Composite 2D Detail
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Solution Overview
Problem
Existing methods for increasing the resolution of composite two-dimensional images from tomographic images result in partial loss of morphological information of structures extending in the depth direction, and increase data processing loads such as processing time and memory requirements.
Innovation Solution
An image processing device and method that selectively enhances the resolution of target regions in tomographic images, generating a high-definition composite two-dimensional image by increasing the resolution of specific regions of interest while maintaining lower resolution in other areas, using super-resolution techniques and weighted averaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the resolution of all tomographic images is increased, then the morphology of details of structures of interest can be expressed in high definition, but the processing time and computational load increase significantly
Solution Approach 1:
The patent applies local quality by selectively enhancing the resolution of specific regions containing structures of interest while maintaining lower resolution in other areas. The processor identifies target regions based on anatomical features or user selection and applies super-resolution processing only to these regions, thereby achieving high-definition morphology expression where needed while minimizing overall processing time and computational load.
2Measurement precision
If the resolution of all tomographic images is increased, then high-definition composite two-dimensional images can be generated, but the memory capacity and data transmission requirements increase
Solution Approach 1:
The patent reduces data amount by applying resolution enhancement only to specific target regions rather than entire images. The processor generates high-resolution data only where structures of interest are located, while other regions remain at lower resolution, thereby significantly reducing memory capacity requirements and data transmission bandwidth while preserving diagnostic quality in critical areas.
3Measurement precision
If resolution enhancement is applied to all tomographic images, then detailed morphology is preserved, but the processing complexity and computational resources required increase
Solution Approach 1:
The patent simplifies processing complexity by implementing a selective enhancement strategy. The processor first identifies target regions containing structures of interest, then applies super-resolution algorithms only to these regions. This localized approach reduces the overall computational complexity compared to processing entire images, while still achieving high-definition morphological detail where clinically relevant.
Solution Approach 2:
The patent applies segmentation by dividing the tomographic images into target regions (containing structures of interest) and non-target regions. The processor separately handles these segments, applying resolution enhancement only to target regions. This segmentation strategy reduces processing complexity by breaking down the large-scale problem into smaller, manageable sub-problems that can be processed more efficiently.
Data Source
AI summary
An image processing device includes a processor and a memory that is provided in or connected to the processor. The processor executes a region selection process of selecting a portion of a plurality of tomographic images, which indicate a plurality of tomographic planes of an object, respectively, and have a first resolution, as a target region to be set to a second resolution higher than the first resolution, a resolution enhancement process of increasing the resolution of the target region to the second resolution to generate a high-resolution partial image, and a composite two-dimensional image generation process of generating a high-resolution composite two-dimensional image having the second resolution, using the high-resolution partial image.