System, method, and computer-accessible medium for generating magnetic resonance imaging-based anatomically guided positron emission tomography reconstruction images with a convolutional neural network
US11481934B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 10, 2019 |
| Grant date | Oct 25, 2022 |
| Priority date | — |
| Expiry date | Jul 4, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2211/408
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An exemplary system, method and computer-accessible medium for generating an image(s) of a portion(s) of a patient(s) can be provided, which can include, for example, receiving first information associated with a combination of positron emission tomography (PET) information and magnetic resonance imaging (MRI) information, generating second information by applying a convolutional neural network(s) (CNN) to the first information, and generating the image(s) based on the second information. The PET information can be fluorodeoxyglucose PET information. The CNN(s) can include a plurality of convolution layers and a plurality of parametric activation functions. The parametric activation functions can include, e.g., a plurality of parametric rectified linear units. Each of the convolution layers can include, e.g., a plurality of filter kernels. The PET information can be reconstructed using a maximum likelihood estimation (MLE) procedure to generate a MLE image.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.