System and methods for inferring thickness of object classes of interest in two-dimensional medical images using deep neural networks
US12361553B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 30, 2023 |
| Grant date | Jul 15, 2025 |
| Priority date | — |
| Expiry date | Oct 30, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and systems are provided for inferring thickness and volume of one or more object classes of interest in two-dimensional (2D) medical images, using deep neural networks. In an exemplary embodiment, a thickness of an object class of interest may be inferred by acquiring a 2D medical image, extracting features from the 2D medical image, mapping the features to a segmentation mask for an object class of interest using a first convolutional neural network (CNN), mapping the features to a thickness mask for the object class of interest using a second CNN, wherein the thickness mask indicates a thickness of the object class of interest at each pixel of a plurality of pixels of the 2D medical image; and determining a volume of the object class of interest based on the thickness mask and the segmentation mask.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.