Systems and methods for image segmentation using a scalable and compact convolutional neural network
US10783640B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 12, 2018 |
| Grant date | Sep 22, 2020 |
| Priority date | — |
| Expiry date | Feb 7, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30004
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments of the disclosure provide systems and methods for segmenting a medical image. An exemplary system includes a communication interface configured to receive the medical image acquired by an image acquisition device. The system further includes a memory configured to store a multi-level learning network including at least a first convolution block and a second convolution block. The second convolution block has at least one convolution layer. The system also includes a processor. The processor is configured to determine a first feature map by applying the first convolution block to the medical image, and determine a second feature map by applying the second convolution block to the first feature map. The processor is further configured to determine a first level feature map by concatenating the first feature map and the second feature map. The processor is also configured to obtain a first level segmented image based on the first level feature map.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.