Machine learning systems and method for assessment, healing prediction, and treatment of wounds
US10783632B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 9, 2020 |
| Grant date | Sep 22, 2020 |
| Priority date | — |
| Expiry date | Jan 9, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30096
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
Machine learning systems and methods are disclosed for prediction of wound healing, such as for diabetic foot ulcers or other wounds, and for assessment implementations such as segmentation of images into wound regions and non-wound regions. Systems for assessing or predicting wound healing can include a light detection element configured to collect light of at least a first wavelength reflected from a tissue region including a wound, and one or more processors configured to generate an image based on a signal from the light detection element having pixels depicting the tissue region, determine reflectance intensity values for at least a subset of the pixels, determine one or more quantitative features of the subset of the plurality of pixels based on the reflectance intensity values, and generate a predicted or assessed healing parameter associated with the wound over a predetermined time interval.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.