Method for learning threshold value

US12249066B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-12249066-B2
Application numberUS-201917622493-A
CountryUS
Kind codeB2
Filing dateJul 12, 2019
Priority dateJul 12, 2019
Publication dateMar 11, 2025
Grant dateMar 11, 2025

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Abstract

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The present invention has been made in view of the foregoing, and an object thereof is to provide a method for learning a threshold that can provide a more objective threshold applied to pixels in the mammography image. The present invention provides a method for learning a threshold value applied to pixels in a mammography image comprising: an acquiring step; and a learning step, wherein in the acquiring step, the mammography image is acquired, in the learning step, a relationship between the mammography image and a mammary gland pixel estimation threshold is learned, the mammary gland pixel estimation threshold is a threshold value used to calculate a mammary gland pixel area of each pixel of a mammary gland region in the mammography image, and the mammary gland pixel area is a value indicating a degree of a mammary gland pixel-likeness of the pixel in the mammography image.

First claim

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The invention claimed is: 1. A method for learning a threshold value applied to pixels in a mammography image comprising: an acquiring step; a histogram generation step; and a learning step, wherein in the acquiring step, the mammography image is acquired, in the histogram generation step, first to third histograms are generated, the first histogram is a histogram of a pixel value of each pixel in the mammography image, the second histogram is a histogram of a pixel value of each pixel in a mammary gland region in the mammography image, and the third histogram is a histogram of a mammary gland region probability of each pixel in the mammography image, the mammary gland region probability indicates a probability that each pixel in the mammography image is in the mammary gland region, in the learning step, a relationship between the first to third histograms and a mammary gland pixel estimation threshold is learned, the mammary gland pixel estimation threshold is a threshold value used to calculate a mammary gland pixel area of each pixel of the mammary gland region in the mammography image, and the mammary gland pixel area is a value indicating a degree of a mammary gland pixel-likeness of the pixel in the mammography image. 2. The method of claim 1 further comprising a mammary gland density acquiring step, wherein in the acquiring step, a correct mammary gland density in the mammary gland region is further acquired, in the mammary gland density acquiring step, a calculated mammary gland density in the mammary gland region is acquired based on the mammography image and the mammary gland pixel estimation threshold, in the learning step, the relationship is learned based on the correct mammary gland density, and the calculated mammary gland density or the mammary gland pixel estimation threshold output in the learning step. 3. The method of claim 2 , wherein in the learning step, a relationship between the mammography image and a mammary gland pixel estimation tilt is further learned, the mammary gland pixel estimation threshold is a threshold of a predetermined threshold function, the mammary gland pixel estimation tilt is a tilt of the threshold function at the mammary gland pixel estimation threshold, the threshold function is a function that associates a pixel value of each pixel in the mammary gland region with the mammary gland pixel area of each such pixel, and in the mammary gland density acquiring step, the mammary gland pixel area of each pixel in the mammary gland region is calculated based on the threshold function, the mammary gland pixel estimation threshold, and the mammary gland pixel estimation tilt, and the calculated mammary gland density is acquired based on the sum of the mammary gland pixel area. 4. The method of claim 1 , wherein the mammary gland region is a narrower region than an entire breast in the mammography image. 5. A method for learning a threshold value applied to pixels in a mammography image comprising: an acquiring step; and a learning step, wherein in the acquiring step, the mammography image is acquired, in the learning step, a relationship between the mammography image and a mammary gland pixel estimation threshold is learned, the mammary gland pixel estimation threshold is a threshold value used to calculate a mammary gland pixel area of each pixel of a mammary gland region in the mammography image, and the mammary gland pixel area is a value indicating a degree of a mammary gland pixel-likeness of the pixel in the mammography image, the method further comprising a mammary gland density acquiring step, wherein in the acquiring step, a correct mammary gland density in the mammary gland region is further acquired, in the mammary gland density acquiring step, a calculated mammary gland density in the mammary gland region is acquired based on the mammography image and the mammary gland pixel estimation threshold, in the learning step, the relationship is learned based on the correct mammary gland density, and the calculated mammary gland density or the mammary gland pixel estimation threshold output in the learning step, in the learning step, a relationship between the mammography image and a mammary gland pixel estimation tilt is further learned, the mammary gland pixel estimation threshold is a threshold of a predetermined threshold function, the mammary gland pixel estimation tilt is a tilt of the threshold function at the mammary gland pixel estimation threshold, the threshold function is a function that associates a pixel value of each pixel in the mammary gland region with the mammary gland pixel area of each such pixel, and in the mammary gland density acquiring step, the mammary gland pixel area of each pixel in the mammary gland region is calculated based on the threshold function, the mammary gland pixel estimation threshold, and the mammary gland pixel estimation tilt, and the calculated mammary gland density is acquired based on the sum of the mammary gland pixel area. 6. The method of claim 5 , wherein the mammary gland region is a narrower region than an entire breast in the mammography image.

Assignees

Inventors

Classifications

  • Mammography; Breast · CPC title

  • Training; Learning · CPC title

  • Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns · CPC title

  • Involving statistics of pixels or of feature values, e.g. histogram matching · CPC title

  • by performing operations within image blocks; by using histograms, e.g. histogram of oriented gradients [HoG]; by summing image-intensity values; Projection analysis · CPC title

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What does patent US12249066B2 cover?
The present invention has been made in view of the foregoing, and an object thereof is to provide a method for learning a threshold that can provide a more objective threshold applied to pixels in the mammography image. The present invention provides a method for learning a threshold value applied to pixels in a mammography image comprising: an acquiring step; and a learning step, wherein…
Who is the assignee on this patent?
Eizo Corp
What technology area does this patent fall under?
Primary CPC classification G06T7/0012. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Mar 11 2025 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 3 related publications on this page (citations in our corpus or others sharing the same primary CPC).