Brain Atrophy Rate Calculation Using Standard Image Similarity
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Solution Overview
Problem
When multiple past brain images are available for the same patient, selecting the appropriate image for calculating brain atrophy rate is challenging, as the atrophy rate can vary depending on which image is chosen, leading to inaccurate calculations if not properly selected.
Innovation Solution
A medical image processing apparatus that acquires a target brain image and multiple past brain images, calculates similarity with a standard brain image, and selects a past brain image with a similarity threshold and closest imaging date as a reference image, allowing for accurate atrophy rate calculation by using this reference image in conjunction with the target image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple past brain images are used for calculating atrophy rate, then more data is available for analysis, but the accuracy of atrophy rate calculation deteriorates due to uncertainty in selecting the appropriate reference image
Solution Approach 1:
The patent changes the selection criterion from temporal proximity (closest to current date) to similarity-based selection (closest to standard brain image). By using similarity metrics such as correlation coefficients or structural similarity indices between each past image and the standard brain image, the system identifies the most appropriate reference image that best represents normal brain structure, thereby improving atrophy rate calculation accuracy despite having multiple past images available.
Solution Approach 2:
The patent introduces a standard brain image as an intermediary reference against which all past brain images are compared. This standard image serves as a mediator to objectively evaluate and select the most suitable past image for atrophy rate calculation, eliminating the ambiguity of direct comparison between multiple past images and ensuring consistent, accurate measurements.
2Loss of time
If the closest past image to current date is selected as reference, then temporal relevance is improved, but accuracy of atrophy rate calculation deteriorates if the brain has already undergone atrophy before that image
Solution Approach 1:
The patent changes the selection parameter from temporal distance (time-based) to similarity metric (structure-based). Instead of automatically selecting the past image closest in time to the current image, the system evaluates each past image's similarity to the standard brain image using metrics like correlation coefficients. This ensures selection of a reference image that reflects normal brain structure, even if it is not the temporally closest one.
Solution Approach 2:
The patent performs preliminary comparison and evaluation of multiple past brain images against the standard brain image before selecting the reference image. By pre-assessing the similarity of each past image to the standard and identifying the one with the highest similarity, the system ensures that the selected reference image truly represents normal brain structure, avoiding the pitfall of selecting an already-atrophied image simply because it is temporally closest.
3Duration of action of stationary object
If the oldest past image is selected as reference, then coverage of atrophy progression is improved, but accuracy deteriorates due to mixing of illness-related and normal aging atrophy
Solution Approach 1:
The patent changes the selection criterion from temporal extremity (oldest image) to similarity-based selection (closest to standard). By using similarity metrics to evaluate each past image against the standard brain image, the system identifies the image that best represents normal brain structure, regardless of its age. This prevents the conflation of pathological atrophy with normal aging changes, ensuring accurate atrophy rate measurement.
Solution Approach 2:
The standard brain image serves as an intermediary reference that objectively evaluates each past image's deviation from normal structure. By comparing each past image to this standard mediator and selecting the one with highest similarity, the system isolates pathological atrophy from normal aging changes, even when using images spanning long time periods.
4Measurement precision
If similarity calculation with standard brain image is performed, then selection accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent transforms the complex problem of selecting the best reference image from multiple candidates into a simpler similarity calculation problem. By defining specific similarity metrics (correlation coefficients, structural similarity indices) between each past image and the standard brain image, the system converts a subjective selection process into an objective, computable parameter that can be efficiently calculated and compared.
Data Source
AI summary
In a medical image processing apparatus, a medical image processing method, and a medical image processing program, in a case where there are a plurality of past brain images, it is possible to select a past brain image with which the atrophy rate of the brain can be accurately calculated. An image acquisition unit acquires a target brain image Bt as a diagnostic target and a plurality of past brain images Bpi, which have earlier imaging dates and times than the target brain image Bt, for the same subject. A similarity calculation unit calculates the similarity between each of the plurality of past brain images Bpi and a standard brain image Bs. A selection unit selects a reference brain image B0 serving as a reference for calculating the amount of change of the brain from the plurality of past brain images Bpi.