Automatic spatial context based multi-object segmentation in 3D images
US9218524B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 25, 2013 |
| Grant date | Dec 22, 2015 |
| Priority date | — |
| Expiry date | Jul 19, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/033
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and systems for automatic classification of images of internal structures of human and animal bodies. A method includes receiving a magnetic resonance (MR) image testing model and determining a testing volume of the testing model that includes areas of the testing model to be classified as bone or cartilage. The method includes modifying the testing model so that the testing volume corresponds to a mean shape and a shape variation space of an active shape model and producing an initial classification of the testing volume by fitting the testing volume to the mean shape and the shape variation space. The method includes producing a refined classification of the testing volume into bone areas and cartilage areas by refining the boundaries of the testing volume with respect to the active shape model and segmenting the MR image testing model into different areas corresponding to bone areas and cartilage areas.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.