Autoencoder Site-Specific Distributed Representation for Abnormality Detection
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Solution Overview
Problem
In abnormality determination using distributed representations, the encoded information becomes a black box, making it impossible to control or identify which site information is affecting which part of the representation.
Innovation Solution
A calculation program and device that utilize an autoencoder to acquire first and second distributed representations, allowing for the analysis of which site contributes to the distributed representation by processing partial images and integrating site-specific information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed representation encoding is used for abnormality determination, then information compression and processing efficiency are improved, but the encoded information becomes a black box making site information identification impossible
Solution Approach 1:
The patent divides the distributed representation into site-specific distributed representations, where each site (e.g., organ, tissue, lesion) has its own dedicated representation space. This segmentation allows the system to maintain processing efficiency through distributed encoding while enabling identification of which site information contributes to each part of the representation by examining the corresponding site-specific components.
2Measurement precision
If comprehensive distributed representation is used for abnormality determination, then determination accuracy is improved, but control over which site information affects which representation part becomes impossible
Solution Approach 1:
The patent introduces site-specific projection matrices as intermediary components that control the transformation from input image features to site-specific distributed representations. These projection matrices serve as controllable intermediaries that enable the system to maintain high determination accuracy while allowing explicit control over which site information is encoded in each representation, making the encoding process transparent and adjustable.
Data Source
AI summary
A non-transitory computer-readable recording medium stores therein a calculation program that causes a computer to execute a process including acquiring a first distributed representation of a partial image corresponding to a specific site of an object to be examined included in each of a plurality of images, by executing machine learning performed by an autoencoder using the partial image of an area corresponding to the specific site, for each of one or more specific sites, and acquiring a second distributed representation of the plurality of images, based on the first distributed representation and a result of machine learning performed by the autoencoder, using the plurality of images, wherein abnormality determination on the object to be examined included in an image to be determined is executed, based on the first distributed representation and the second distributed representation.