18424102. DIAGNOSIS SUPPORT DEVICE, LEARNING DEVICE, DIAGNOSIS SUPPORT METHOD, LEARNING METHOD, AND PROGRAM simplified abstract (Nikon Corporation)
Contents
DIAGNOSIS SUPPORT DEVICE, LEARNING DEVICE, DIAGNOSIS SUPPORT METHOD, LEARNING METHOD, AND PROGRAM
Organization Name
Inventor(s)
Toshihide Kurihara of Tokyo (JP)
Kanato Masayoshi of Tokyo (JP)
DIAGNOSIS SUPPORT DEVICE, LEARNING DEVICE, DIAGNOSIS SUPPORT METHOD, LEARNING METHOD, AND PROGRAM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18424102 titled 'DIAGNOSIS SUPPORT DEVICE, LEARNING DEVICE, DIAGNOSIS SUPPORT METHOD, LEARNING METHOD, AND PROGRAM
The patent application describes a device for supporting diagnosis that can analyze fundus images of a subject's eye to identify areas of abnormality in blood circulation.
- Reception unit receives fundus image of subject eye
- Identification unit uses trained model to recognize abnormality in blood circulation
- Model trained based on fundus image and abnormality specified in fluorescent angiography image
- Output unit provides information on recognized abnormality in fundus image
Potential Applications: - Medical diagnosis and monitoring of eye conditions related to blood circulation abnormalities - Early detection of diseases such as diabetic retinopathy or macular degeneration
Problems Solved: - Enables quick and accurate identification of blood circulation abnormalities in the eye - Facilitates timely intervention and treatment for eye conditions
Benefits: - Improves efficiency and accuracy of diagnosing eye diseases - Enhances patient outcomes through early detection and intervention
Commercial Applications: - Ophthalmology clinics and hospitals can use this device for routine eye examinations - Pharmaceutical companies may utilize the technology for clinical trials and research on eye diseases
Questions about the Technology: 1. How does the device differentiate between normal and abnormal blood circulation in the fundus image? 2. What are the limitations of using fluorescent angiography images for training the model in this device?
Frequently Updated Research: - Stay updated on advancements in fundus imaging technology and machine learning algorithms for eye disease diagnosis.
Original Abstract Submitted
A device for supporting diagnosis has: a reception unit that is configured to receive a fundus image of a subject eye; an identification unit provided with a trained model that is configured to recognize, in the fundus image of the subject eye, an area of abnormality in blood circulation, wherein the model has been trained based upon an image of a fundus and an area of abnormality in blood circulation specified in a fluorescent angiography image of the fundus; and an output unit that is configured to output information relating to the area of abnormality in blood circulation recognized in the fundus image of the subject eye.
