Apparatus and method for image segmentation using a deep convolutional neural network with a nested U-structure
US11836928B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 28, 2020 |
| Grant date | Dec 5, 2023 |
| Priority date | — |
| Expiry date | Jan 21, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30004
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A non-transitory computer readable storage medium has instructions executed by a processor to receive an ultrasound image. The ultrasound image is applied to a sequence of encoders where each encoder in the sequence of encoders performs convolution neural network processing of a down-sampled version of the ultrasound image from a prior encoder, the sequence of encoders form a first dimension. The ultrasound image is applied to a transition encoder with an orthogonal dimension to the first dimension. The ultrasound image is applied to a sequence of decoders where each decoder in the sequence of decoders performs convolution neural network processing of an up-sampled version of the ultrasound image from a prior decoder, the sequence of decoders form a second parallel dimension to the first dimension. Encoder and decoder configurations and the first dimension, the orthogonal dimension and the second parallel dimension thereby define a nested U network architecture. Probability segmentation maps are produced from paired encoders and decoders in the sequence of encoders and the sequence of decoders. The probability segmentation maps are combined to form a final probability segmentation …
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