Characterizing intra-tumoral heterogeneity for response and outcome prediction using radiomic spatial textural descriptor (RADISTAT)
US10650515B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 23, 2018 |
| Grant date | May 12, 2020 |
| Priority date | — |
| Expiry date | Sep 25, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments access an image of a region of interest (ROI) demonstrating cancerous pathology; extract radiomic features from the ROI; define a radiomic feature expression scene based on the ROI and radiomic features; generate a cluster map by superpixel clustering the expression scene; generate an expression map by repartitioning the cluster map into expression levels; compute a textural and spatial phenotypes for the expression map based on the expression levels; construct a radiomic spatial textural (RADISTAT) descriptor by concatenating the textural and spatial phenotypes; provide the RADISTAT descriptor to a machine learning classifier; receive, from the machine learning classifier, a first probability that the ROI is a responder or non-responder, or a second probability that the ROI will experience long-term survival or short-term survival, based, at least in part, on the RADISTAT descriptor; and generate a classification of the ROI as a responder or non-responder, or long-term survivor or short-term survivor.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.