Breast Density Derivation Using Multi-State Radiographic Fat Tissue Pixels
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Solution Overview
Problem
Existing techniques for deriving the percentage of mammary glands in breast radiographic images face challenges when a fat tissue pixel, essential for estimation, is not included in the image due to varying breast compression states.
Innovation Solution
An image processing apparatus and method that acquire multiple radiographic images of the same breast in different compression states, and derive the percentage of mammary glands based on the amount of incident radiation from a fat tissue pixel included in one of the images, allowing for accurate estimation even when the fat tissue pixel is not present in all images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single radiographic image is used to derive the percentage of mammary glands, then the processing time is reduced, but the accuracy of derivation fails when fat tissue pixel is not included in the image
Solution Approach 1:
The system performs preliminary acquisition of multiple radiographic images under different compression states before the actual derivation process. By preparing these images in advance, the system ensures that at least one image contains a usable fat tissue pixel, thereby guaranteeing accurate derivation without requiring complex real-time adjustments during processing.
Solution Approach 2:
The system changes the compression state parameter of the breast imaging to generate multiple radiographic images with different tissue distributions. By varying this physical parameter, the system increases the probability of capturing images where fat tissue pixels are visible, thus improving derivation accuracy without adding complex processing algorithms.
2Measurement precision
If multiple radiographic images in different compression states are acquired, then the accuracy of mammary gland percentage derivation is improved, but the processing time and data volume increase
Solution Approach 1:
The system extracts only the essential information (fat tissue pixel values) from the multiple acquired images rather than processing all image data. By selectively extracting and utilizing only the necessary parameters from images containing fat tissue pixels, the system maintains high derivation accuracy while significantly reducing processing time and computational load.
Solution Approach 2:
The system acquires more images than strictly necessary (excessive action) but processes only the subset of images that contain usable fat tissue pixels (partial action). This approach ensures that the derivation accuracy is maintained by having sufficient data options, while avoiding the time penalty of processing all acquired images by selectively using only those needed.
3Ease of operation
If fat tissue pixel is assumed to be present in all radiographic images, then the processing is simplified, but the reliability of the system deteriorates when the assumption is violated
Solution Approach 1:
The system implements a feedback mechanism that checks whether fat tissue pixels are actually present in the acquired radiographic images before proceeding with derivation. Based on this feedback, the system dynamically adjusts its processing approach - using simple processing when fat tissue pixels are present and switching to alternative methods when they are absent, thereby maintaining both simplicity and reliability.
Solution Approach 2:
The system transitions from a static assumption (fat tissue pixel always present) to a dynamic approach where the processing method adapts based on the actual content of acquired images. By making the system flexible and adaptive to varying image conditions, it maintains operational simplicity in normal cases while ensuring reliability in exceptional cases where fat tissue pixels are missing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables high-accuracy derivation of mammary gland percentage even in cases where the fat tissue pixel is not included in the radiographic image, improving the reliability of breast density assessment.
Implementation Method 1
a value of a pixel corresponding to a direct region, that is, a region to which the radiation is directly emitted without passing through the breast
Data Source
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Figure 3A
AI summary
An image processing apparatus includes: an acquisition unit that acquires a plurality of radiographic images of the same breast which have captured in a plurality of different states related to compression of the breast; and a derivation unit that derives, on the basis of an amount of incident radiation derived from a value of a fat tissue pixel in a radiographic image in which the fat tissue pixel obtained by a portion of the breast which is estimated to be composed of only fat tissues is included in a breast image among the plurality of radiographic images acquired by the acquisition unit, a percentage of mammary glands of a breast image in a radiographic image different from the radiographic image used to derive the amount of incident radiation.