Systems and methods for noise reduction in medical images with deep neural networks
US10635943B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 7, 2018 |
| Grant date | Apr 28, 2020 |
| Priority date | — |
| Expiry date | Nov 23, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and systems are provided for reducing noise in medical images with deep neural networks. In one embodiment, a method for training a neural network comprises transforming each of a plurality of initial image data sets not acquired by a medical imaging modality into a target image data set, wherein each target image data set is in a format specific to the medical imaging modality, corrupting each target image data set to generate a corrupted image data set, and training the neural network to map each corrupted image data set to the corresponding target image data set. In this way, the high-resolution of digital non-medical photographs or images can be leveraged for the enhancement or correction of medical images, and the trained neural network can be used to reduce noise and image artifacts in medical images acquired by the medical imaging modality.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.