Fast synthetic Haralick texture generation for histology images
US11295112B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 23, 2020 |
| Grant date | Apr 5, 2022 |
| Priority date | — |
| Expiry date | Sep 27, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments discussed herein facilitate training deep learning models to generate synthetic versions of histological texture features and employing such deep learning models. One example embodiment is an apparatus configured to convert a stained histological image to grayscale; extract patches from the grayscale image; for each patch of the plurality of patches: provide that patch to a deep learning model trained to generate a synthetic version of a texture feature; and obtain an associated patch from the deep learning model that indicates an associated value of the synthetic version of the histology texture feature for each pixel of that patch; and merge the associated patches for each patch of the plurality of patches to generate an associated feature map for the stained histological image, wherein the associated feature map indicates the associated value of the synthetic version of the histology texture feature for each pixel of the plurality of pixels.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.