US Patent Application 18031675. Image Processing Apparatus, Image Processing Method, and Program simplified abstract
Contents
Image Processing Apparatus, Image Processing Method, and Program
Organization Name
Inventor(s)
Image Processing Apparatus, Image Processing Method, and Program - A simplified explanation of the abstract
This abstract first appeared for US patent application 18031675 titled 'Image Processing Apparatus, Image Processing Method, and Program
Simplified Explanation
The patent application describes a medical image processing apparatus and method that improve the accuracy of specialized learning based on a doctor's knowledge using conventional features.
- The apparatus calculates a predetermined feature value for each image in a first image group and selects an image based on this value to form a second image group.
- A feature extraction unit then performs learning on the second image group using a feature generation network to extract a new feature.
- This new feature enhances the accuracy of specialized learning in medical image processing.
- The invention aims to improve the accuracy of medical image analysis and diagnosis by incorporating the doctor's knowledge into the learning process.
- By utilizing both conventional features and the newly extracted features, the apparatus can provide more accurate and reliable results in medical image processing.
Original Abstract Submitted
Provided are a medical image processing apparatus and a medical image processing method capable of implementing specialized learning with higher accuracy in a case where the specialized learning is performed on a plurality of conventional features based on knowledge of a doctor. An image processing apparatus according to the present invention includes: an image group conversion unit that calculates a value of a predetermined feature (first feature) for each image constituting an input first image group, selects an image from the first image group on the basis of the value of the feature, and sets the image as an image of a second image group; and a feature extraction unit that extracts a new feature (second feature) by performing learning on the second image group generated by the image group conversion unit using a feature generation network.
