Medical image processing apparatus, medical image processing method and computer-readable medium

Patent metadata

Field	Value
Publication number	US-11922601-B2
Application number	US-202117223702-A
Country	US
Kind code	B2
Filing date	Apr 6, 2021
Priority date	Oct 10, 2018
Publication date	Mar 5, 2024
Grant date	Mar 5, 2024

Abstract

A medical image processing apparatus includes: an obtaining unit configured to obtain a first image that is a motion contrast en-face image of an eye to be examined; and an image quality improving unit configured to generate a second image with at least one of lower noise and higher contrast than the obtained first image using the obtained first image as input data that is input into an image quality improving engine, wherein the image quality improving engine includes a machine learning engine that has been obtained by using training data including a second image with at least one of lower noise and higher contrast than a first image that is a motion contrast en-face image of an eye to be examined.

First claim

What is claimed is:

1. A medical image processing apparatus comprising:
an obtaining unit configured to obtain a first image that is a motion contrast en-face image corresponding to at least partial depth range of a depth range of an eye to be examined; and
a generating unit configured to generate a second image with at least one of lower noise and higher contrast than the first image using the first image as input data that is input into an image quality improving engine, wherein the image quality improving engine includes a machine learning engine that has been obtained by using training data including third images that are a plurality of motion contrast en-face images corresponding to a plurality of partial depth ranges in a depth range of an eye to be examined and fourth images with at least one of lower noise and higher contrast than the third images, and wherein the plurality of partial depth ranges are different from each other.

2. The medical image processing apparatus according to claim 1 , wherein:
the image quality improving engine includes the machine learning engine that has been obtained by using training data including an image obtained by performing averaging processing.

3. The medical image processing apparatus according to claim 1 , wherein:
the image quality improving engine includes the machine learning engine that has been obtained by using training data including an image obtained by OCTA imaging performed by an OCT imaging apparatus with higher performance than an OCT imaging apparatus used for OCTA imaging of the third images, or an image obtained by an OCTA imaging step that includes a greater number of steps than an OCTA imaging step used for obtaining the third images.

4. The medical image processing apparatus according to claim 1 , wherein:
the image quality improving unit generates the second image with at least one of lower noise and higher contrast than the first image by dividing the first image into a plurality of two-dimensional images and inputting the plurality of two-dimensional images into the image quality improving engine, and integrating a plurality of output images from the image quality improving engine.

5. The medical image processing apparatus according to claim 4 , wherein:
the image quality improving engine includes the machine learning engine that has been obtained by using training data including an image pair having a corresponding positional relationship to each other, and
the image quality improving unit divides the first image into a plurality of two-dimensional images having an image size corresponding to an image size of the image pair and inputs the plurality of two-dimensional images to the image quality improving engine.

6. The medical image processing apparatus according to claim 4 , wherein:
the image quality improving engine includes the machine learning engine that has been obtained by using training data that, with respect to a region including an image and an outer periphery of the image, includes images of a plurality of partial regions set so that parts of partial regions that are adjacent overlap with each other.

7. The medical image processing apparatus according to claim 1 , wherein:
the image quality improving engine includes the machine learning engine that has been obtained by using training data including an image obtained by adding noise to an image.

8. The medical image processing apparatus according to claim 1 , wherein:
the image quality improving engine includes the machine learning engine that has been obtained by using training data including an image pair obtained by adding noise of different patterns from each other to an image.

9. The medical image processing apparatus according to claim 1 , wherein:
the image quality improving engine includes the machine learning engine that has been obtained by using training data including an image pair obtained by adding noise of different patterns from each other to an image obtained by performing averaging processing.

10. The medical image processing apparatus according to claim 1 , further comprising:
a wide-angle image generating unit configured to generate a wide-angle image using a plurality of the second images obtained from a plurality of the first images, the plurality of first images being obtained by performing OCTA imaging of different positions of an eye to be examined so that partial regions of motion contrast en-face images that are adjacent overlap with each other.

11. The medical image processing apparatus according to claim 1 , wherein:
the image quality improving engine includes the machine learning engine that has been obtained by using training data including a plurality of motion contrast en-face images corresponding to different depth ranges of an eye to be examined; and
the obtaining unit obtains a motion contrast en-face image corresponding to a partial depth range of a long depth range including the different depth ranges as the first image that is input into the image quality improving engine.

12. The medical image processing apparatus according to claim 1 , further comprising:
a determining unit configured to determine whether or not the image quality improving unit can generate the second image using the image quality improving engine with respect to the first image,
wherein the determining unit performs the determination based on at least one of an imaged site, an imaging system, an imaging angle of view and an image size of the first image.

13. The medical image processing apparatus according to claim 1 , wherein:
the image quality improving unit includes a plurality of image quality improving engines that have been obtained by using different training data from each other, and
each of the plurality of image quality improving engines has performed learning using different training data from each other with respect to at least one of an imaged site, an imaging angle of view, and an image resolution, and
the image quality improving unit generates the second image with at least one of lower noise and higher contrast than the first image using the image quality improving engine that corresponds to at least one of an imaged site, an imaging angle of view, and an image resolution of the first image.

14. The medical image processing apparatus according to claim 1 , wherein:
the image quality improving unit includes a plurality of image quality improving engines that have been obtained by using different training data from each other, and
the image quality improving unit generates the second image with at least one of lower noise and higher contrast than the first image using the first image as input data that is input into an image quality improving engine selected in accordance with an instruction of an examiner among the plurality of image quality improving engines.

15. The medical image processing apparatus according to claim 1 , wherein:
the image quality improving unit includes a plurality of image quality improving engines that have been obtained by using different training data from each other, and
the image quality improving unit generates a plurality of second images with at least one of lower noise and higher contrast than the first image using the first image as input data that is input into the plurality of image quality improving engines; and
the medical image processing apparatus outputs at least one image among the plurality of second images in accordance with an instruction of an examiner.

16. The medical image processing apparatus according to claim 1 , further comprising:
an evaluating unit config

Assignees

• Canon Kk

Inventors

• Iwase Yoshihiko
• Yamazoe Manabu
• Mizobe Hideaki
• Uchida Hiroki
• Tomita Ritsuya

Classifications

• G06N3/094

  Adversarial learning · CPC title

• G06N3/0464

  Convolutional networks [CNN, ConvNet] · CPC title

• G06N3/0475

  Generative networks · CPC title

• G06N3/09

  Supervised learning · CPC title

• G06T5/002 Primary

  Physics · mapped topic