INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND PROGRAM

• US 20200135328A1
• 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 11,710,567 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 18/2178 based on feedback of a supervisor
• CPC Class Codes: G06F 18/41 Interactive pattern learning with a human teacher
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 3/084 Backpropagation, e.g. using gradient descent
• CPC Class Codes: G06T 2207/10081 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 2207/20104 Interactive definition of region of interest [ROI]
• CPC Class Codes: G06T 2207/30061 Lung
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06V 10/7784 based on feedback from supervisors
• CPC Class Codes: G06V 10/7788 the supervisor being a human, e.g. interactive learning with a human teacher
• CPC Class Codes: G06V 2201/03 Recognition of patterns in medical or anatomical images
• CPC Class Codes: G06V 2201/031 of internal organs
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 40/20 : for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Provided are an information processing apparatus, an information processing method, and a program capable of accumulating appropriate relearning data. An information processing apparatus includes an input unit that inputs input data to a learned model acquired in advance through machine learning using learning data, an acquisition unit that acquires output data output from the learned model through the input using the input unit, a reception unit that receives correction performed by a user for the output data acquired by the acquisition unit, and a storage controller that performs control for storing, as relearning data of the learned model, the input data and the output data that reflects the correction received by the reception unit in a storage unit in a case where a value indicating a correction amount acquired by performing the correction for the output data is equal to or greater than a threshold value.

Claims

1. An information processing apparatus comprising:

an input unit that inputs input data to a learned model acquired in advance through machine learning using learning data;

an acquisition unit that acquires output data output from the learned model through the input using the input unit;

a reception unit that receives correction performed by a user for the output data acquired by the acquisition unit; and

a storage controller that performs control for storing, as relearning data of the learned model, the input data and the output data that reflects the correction received by the reception unit in a storage unit in a case where a value indicating a correction amount acquired by performing the correction for the output data is equal to or greater than a threshold value.

2. The information processing apparatus according to claim 1,

wherein the value indicating the correction amount is a sum of an absolute value of a ratio of an added portion and an absolute value of a ratio of a deleted portion to and from the output data through the correction.

3. The information processing apparatus according to claim 1,

wherein the input data is image data indicating a medical image, and

the output data is data indicating a region extracted from the image data.

4. The information processing apparatus according to claim 3,

wherein the value indicating the correction amount is a ratio of a sum of an area of an added portion and an area of a deleted portion through the correction performed by the user received by the reception unit to an area of the region indicated by the output data.

5. The information processing apparatus according to claim 3,

wherein the value indicating the correction amount is a ratio of a sum of a volume of an added portion and a volume of a deleted portion through the correction performed by the user received by the reception unit to a volume of the region indicated by the output data.

6. The information processing apparatus according to claim 1,

wherein the output data is a sentence of a medical diagnostic report.

7. The information processing apparatus according to claim 1,

wherein the value indicating the correction amount is the number of times the correction is performed by the user for the output data.

8. The information processing apparatus according to claim 1,

wherein the storage controller performs the control in a case where the user is a user determined as a reliable user in advance.

9. The information processing apparatus according to claim 1,

wherein the threshold value is a value which becomes smaller as a skill level of the user becomes higher.

10. The information processing apparatus according to claim 1,

wherein the threshold value is a value determined depending on a treatment plan of a subject.

11. The information processing apparatus according to claim 1,

wherein the threshold value is 10%.

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

a learning unit that causes the learned model to relearn by using the relearning data stored in the storage unit by the storage controller.

13. An information processing method comprising:

inputting input data to a learned model acquired in advance through machine learning using learning data;

acquiring output data output from the learned model through the input;

receiving correction performed by a user for the acquired output data; and

performing control for storing, as relearning data of the learned model, the input data and the output data that reflects the received correction in a storage unit in a case where a value indicating a correction amount acquired by performing the correction for the output data is equal to or greater than a threshold value.

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

inputting input data to a learned model acquired in advance through machine learning using learning data;

acquiring output data output from the learned model through the input;

receiving correction performed by a user for the acquired output data; and

performing control for storing, as relearning data of the learned model, the input data and the output data that reflects the received correction in a storage unit in a case where a value indicating a correction amount acquired by performing the correction for the output data is equal to or greater than a threshold value.