An electrical tomography image reconstruction method based on a convolutional neural network
A technology of electrical tomography and convolutional neural network, applied in the field of tomography, achieves good noise resistance and generalization ability, and improves accuracy
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment Construction
[0033] An electrical tomography image reconstruction method based on deep learning theory, taking electrical resistance tomography as an example, applies a convolutional neural network structure to solve the image reconstruction problem of one or more inclusions in the measured field. Compared with existing imaging algorithms, this method improves the accuracy and real-time performance of image reconstruction, and has good noise resistance and generalization ability.
[0034] Aiming at solving the inverse problem of electrical tomography, the present invention uses a convolutional neural network to train a large number of relevant samples, and actively learns the complex nonlinear relationship between boundary measurement values and field distributions by continuously adjusting network structure parameters to perform image reconstruction .
[0035] The specific calculation steps are as follows:
[0036] 1. Use the finite element method to solve the positive problem of elect...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com