Image Processing Apparatus, Image Processing Method, and Program
US-2023386033-A1 · Nov 30, 2023 · US
Medical image processing apparatus and medical image processing method
US12315633B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12315633-B2 |
| Application number | US-202217714331-A |
| Country | US |
| Kind code | B2 |
| Filing date | Apr 6, 2022 |
| Priority date | Apr 27, 2021 |
| Publication date | May 27, 2025 |
| Grant date | May 27, 2025 |
How to read this patent
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
- Title
What the patent document calls the invention.
- Abstract
A short plain-language summary of the technical disclosure.
- Assignees and inventors
Who owns or filed the patent and who is credited as inventor.
- Key dates
Filing, priority, publication, and grant dates set the timeline.
- First independent claim
The legal scope of protection — read this for what is actually claimed.
- CPC / IPC classifications
Technology tags used to group this patent with similar filings.
- Citations and related patents
Prior art links and similar publications in this corpus.
Abstract
Official abstract text for this publication.
A medical image processing apparatus and a medical image processing method that can improve extraction accuracy of a tumor region included in a diagnosis target image are provided. The medical image processing apparatus configured to extract a predetermined region from a diagnosis target image includes: an organ extraction unit configured to extract an organ region from the diagnosis target image; and a tumor extraction unit generated by executing machine learning using a known tumor region included in each medical image group as teacher data and using an organ region extracted from the medical image group and the medical image group as input data. The tumor extraction unit is configured to extract a tumor region from the diagnosis target image using the organ region extracted from the diagnosis target image by the organ extraction unit.
First claim
Opening claim text (preview).
What is claimed is: 1. A medical image processing apparatus configured to extract a predetermined region from a diagnosis target image, the medical image processing apparatus comprising: an organ extraction unit configured to extract an organ region from the diagnosis target image; and a tumor extraction unit generated by executing machine learning using a known tumor region included in each medical image group as teacher data and using an organ region extracted from the medical image group and the medical image group as input data, wherein the tumor extraction unit is configured to extract a tumor region from the diagnosis target image using the organ region extracted from the diagnosis target image by the organ extraction unit, wherein the medical image processing apparatus further comprises a feature amount calculation unit configured to calculate a feature amount related to the tumor region extracted by the tumor extraction unit, wherein the feature amount calculated by the feature amount calculation unit includes a tumor-organ feature amount that is a feature amount representing a relation between the organ region extracted from the medical image group, which is extracted by the organ extraction unit, and the tumor region extracted by the tumor extraction unit, and wherein the tumor-organ feature amount includes a distance between the organ region and the tumor region, presence or absence of adhesion between the organ region and the tumor region, and presence or absence of infiltration of the tumor region into the organ region. 2. The medical image processing apparatus according to claim 1 , wherein the organ extraction unit is generated by executing machine learning using a known organ region included in each medical image group as teacher data and using the medical image group as input data, and wherein the input data used for generation of the tumor extraction unit includes the organ region extracted from the medical image group by the organ extraction unit. 3. The medical image processing apparatus according to claim 1 , wherein the feature amount calculated by the feature amount calculation unit includes a tumor property feature amount that is a feature amount related to the tumor region itself extracted by the tumor extraction unit. 4. The medical image processing apparatus according to claim 3 , wherein the tumor property feature amount includes a histogram of a size, a shape, and a pixel value of the tumor region. 5. The medical image processing apparatus according to claim 1 , further comprising a state determination unit configured to determine a state of the tumor region based on the feature amount calculated by the feature amount calculation unit.
Assignees
Inventors
Classifications
- G06T7/0012Primary
Biomedical image inspection · CPC title
Tumor; Lesion · CPC title
Supervised learning · CPC title
Convolutional networks [CNN, ConvNet] · CPC title
for mining of medical data, e.g. analysing previous cases of other patients · CPC title
Patent family
Related publications grouped by family.
External sources
Frequently asked questions
Answers are generated from the same data shown on this page.
- What does patent US12315633B2 cover?
- A medical image processing apparatus and a medical image processing method that can improve extraction accuracy of a tumor region included in a diagnosis target image are provided. The medical image processing apparatus configured to extract a predetermined region from a diagnosis target image includes: an organ extraction unit configured to extract an organ region from the diagnosis target ima…
- Who is the assignee on this patent?
- Hitachi Ltd
- 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 May 27 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 6 related publications on this page (citations in our corpus or others sharing the same primary CPC).