INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND PROGRAM

• US 20200134819A1
• Filed: 10/22/2019
• Published: 04/30/2020
• Est. Priority Date: 10/29/2018
• Status: Active Grant

• Current Assignee: Fujifilm Corporation (Fujifilm Holdings Corporation)
• Original Assignee: Fujifilm Corporation (Fujifilm Holdings Corporation)
• Inventors: YAMADA, Kenta
• Granted Patent: US 11,334,990 B2
• Time in Patent Office: Days
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 3/084 Backpropagation, e.g. using gradient descent
• CPC Class Codes: G06T 2207/10072 Tomographic images
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/20081 Training; Learning
• CPC Class Codes: G06T 2207/20084 Artificial neural networks [ANN]
• CPC Class Codes: G06T 2207/30008 Bone
• CPC Class Codes: G06T 2207/30061 Lung
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/11 Region-based segmentation

Abstract

Provided are an information processing apparatus, an information processing method, and a program capable of accurately extracting a target region from a medical image. An information processing apparatus includes an extraction unit that extracts information indicating a physique of a subject from an image acquired by imaging the subject, a specification unit that specifies a group into which the subject is classified by using the information indicating the physique of the subject extracted by the extraction unit, and a generation unit that generates a learned model for each group through machine learning using, as learning data, image data indicating a medical image acquired by imaging the subject for each group and information indicating a region extracted from the medical image.

Claims

1. An information processing apparatus comprising:

an extraction unit that extracts information indicating a physique of a subject from an image acquired by imaging the subject;

a specification unit that specifies a group into which the subject is classified by using the information indicating the physique of the subject extracted by the extraction unit; and

a generation unit that generates a learned model for each group using, as an input, image data indicating a medical image acquired by imaging the subject for each group and using, as an output, information indicating a region extracted from the medical image through machine learning using, as learning data, the image data indicating the medical image and the information indicating the region.

2. The information processing apparatus according to claim 1, further comprising:

an input unit that inputs image data indicating the medical image to one learned model acquired in advance through the machine learning using, as the learning data, the image data indicating the medical image and the information indicating the region; and

an acquisition unit that acquires the information indicating the region output from the one learned model through the input by the input unit,

wherein the generation unit generates the learned model for each group by causing the one learned model to relearn for each group specified by the specification unit by using, as the learning data, the medical image data input by the input unit and the information indicating the region acquired by the acquisition unit.

3. The information processing apparatus according to claim 1,

wherein the information indicating the physique of the subject is a skeleton of the subject.

4. The information processing apparatus according to claim 1,

wherein the information indicating the physique of the subject is a body surface of the subject.

5. The information processing apparatus according to claim 1,

wherein the image used for extracting the information indicating the physique of the subject is the medical image.

6. The information processing apparatus according to claim 1,

wherein the group is a group into which the subject is classified according to an age, a gender, a race, or a species of the subject.

7. An information processing method comprising:

extracting information indicating a physique of a subject from an image acquired by imaging the subject;

specifying a group into which the subject is classified by using the extracted information indicating the physique of the subject; and

generating a learned model for each group using, as an input, image data indicating a medical image acquired by imaging the subject for each group and using, as an output, information indicating a region extracted from the medical image through machine learning using, as learning data, the image data indicating the medical image and the information indicating the region.

8. A non-transitory computer readable medium storing a program causing a computer to execute a process comprising:

extracting information indicating a physique of a subject from an image acquired by imaging the subject;

specifying a group into which the subject is classified by using the extracted information indicating the physique of the subject; and

generating a learned model for each group using, as an input, image data indicating a medical image acquired by imaging the subject for each group and using, as an output, information indicating a region extracted from the medical image through machine learning using, as learning data, the image data indicating the medical image and the information indicating the region.