18533069. MEDICAL IMAGE DIAGNOSIS SYSTEM, MEDICAL IMAGE DIAGNOSIS METHOD, AND PROGRAM simplified abstract (FUJIFILM CORPORATION)
Contents
- 1 MEDICAL IMAGE DIAGNOSIS SYSTEM, MEDICAL IMAGE DIAGNOSIS METHOD, AND PROGRAM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 MEDICAL IMAGE DIAGNOSIS SYSTEM, MEDICAL IMAGE DIAGNOSIS METHOD, AND PROGRAM - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
MEDICAL IMAGE DIAGNOSIS SYSTEM, MEDICAL IMAGE DIAGNOSIS METHOD, AND PROGRAM
Organization Name
Inventor(s)
MEDICAL IMAGE DIAGNOSIS SYSTEM, MEDICAL IMAGE DIAGNOSIS METHOD, AND PROGRAM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18533069 titled 'MEDICAL IMAGE DIAGNOSIS SYSTEM, MEDICAL IMAGE DIAGNOSIS METHOD, AND PROGRAM
Simplified Explanation
The patent application describes a medical image diagnosis system that helps reduce the burden on doctors when diagnosing a large number of medical images, such as during health checkups. The system includes a processor and memory that stores commands for the processor to execute. The processor first determines if a medical image is normal, and then determines the presence or absence of abnormalities if the image is not normal.
- Medical image diagnosis system to assist doctors in diagnosing a large number of medical images
- Processor and memory used to store and execute commands for image analysis
- First determination of normalcy of medical image
- Second determination of abnormalities if image is not normal
Potential Applications
The technology can be applied in various medical settings where a large number of medical images need to be analyzed, such as in health checkups, screenings, and diagnostic imaging procedures.
Problems Solved
1. Reducing the burden on doctors when diagnosing a large volume of medical images 2. Improving efficiency and accuracy in identifying abnormalities in medical images
Benefits
1. Faster and more accurate medical image diagnosis 2. Enhanced workflow for healthcare professionals 3. Improved patient outcomes through timely detection of abnormalities
Potential Commercial Applications
"Streamlining Medical Image Diagnosis for Healthcare Providers"
Possible Prior Art
There are existing medical image analysis systems that assist doctors in interpreting medical images, but this specific approach of first determining normalcy before analyzing abnormalities may be a novel aspect of this technology.
What are the technical specifications of the processor and memory used in the system?
The technical specifications of the processor and memory used in the system are not provided in the abstract. Further details on the processing power, memory capacity, and speed of the system would be necessary to understand its performance capabilities.
How does the system differentiate between various types of abnormalities in medical images?
The abstract does not elaborate on how the system distinguishes between different types of abnormalities in medical images. Additional information on the algorithms or techniques used for abnormality detection would be needed to understand the system's capabilities in detail.
Original Abstract Submitted
Provided are a medical image diagnosis system, a medical image diagnosis method, and a program which reduce a burden on a doctor in a case of performing image diagnosis on a large number of medical images, such as a health checkup. The problem is solved by a medical image diagnosis system including at least one processor, and at least one memory that stores a command to be executed by the at least one processor, in which the at least one processor performs first determination of determining whether or not a medical image obtained by imaging a subject is normal, and performs second determination of determining presence or absence of an abnormality from the medical image in a case in which it is determined that the medical image is not normal in the first determination.
