Automatic glandular and tubule detection in histological grading of breast cancer
US10445619B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 27, 2017 |
| Grant date | Oct 15, 2019 |
| Priority date | — |
| Expiry date | Mar 16, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30096
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatuses for automatically identifying glandular regions and tubule regions in a breast tissue sample are provided. An image of breast tissue is analyzed to detect nuclei and lumen candidates, identify tumor nuclei and true lumen from the candidates, and group tumor nuclei with neighboring tumor nuclei and lumina to define tubule glandular regions and non-tubule glandular regions of the image. Learnt supervised classifiers, such as random forest classifiers, can be applied to identify and classify the tumor nuclei and true lumina. Graph-cut methods can be applied to group the tumor nuclei and lumina and to define the tubule glandular regions and non-tubule glandular regions. The analysis can be applied to whole slide images and can resolve tubule areas with multiple layers of nuclei.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.