Focus position estimation model generation system, focal position estimation model generation method, focal position estimation model generation program, and focal position estimation model
JP2023055694A5Active Publication Date: 2025-03-18HAMAMATSU PHOTONICS KK
0 Cites 0 Cited by
Patent Information
- Application Number
- JP2022211786
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2021-07-19
- Filing Date
- 2022-12-28
- Publication Date
- 2025-03-18
- Estimated Expiration
- 2042-03-10
AI Technical Summary
Technical Problem
Conventional methods for estimating the appropriate focal position in virtual slide scanners using machine learning are time-consuming, making it difficult to perform short-time learning effectively.
Method used
A feature output model generation system that utilizes machine learning to compare feature values of learning images associated with different focal positions, allowing for the generation of a trained model in a short period of time by adjusting the differences in feature amounts based on focal position information.
Benefits of technology
Enables rapid generation of a trained model for focal position estimation, facilitating quick and accurate image-based estimation of focal positions in virtual slide scanners.
✦ Generated by Eureka AI based on patent content.
Abstract
It is possible to generate a trained model used for image-based estimation, such as estimating focus position, through short-term training. [Solution] The feature output model generation system 20 is a system that receives image-based information as input and generates a feature output model that outputs the features of the image, and includes a training image acquisition unit 21 that acquires multiple training images associated with focus position information relating to the focus position at the time of image capture, and a feature output model generation unit 22 that generates a feature output model from the acquired training images through machine learning, and the feature output model generation unit 22 compares the features of two different training images according to the focus position information associated with the two training images, and performs machine learning based on the comparison results.
Need to check novelty before this filing date? Find Prior Art