Patent ID: 11941813
Assignee: NANTCELL, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A system for performing classification of data based on tensor inputs, the system comprising:
memory storing computer-executable instructions defining a learning network, where the learning network includes a plurality of sequential encoder down-sampling blocks, and the learning network is a segmentation model including deep learning parameters adjusted by comparing segmentation classifications produced by processing cropped training patches using the segmentation model to corresponding specified segmentation classification masks; and
a processor in communication with the memory, the processor configured to execute the computer-executable instructions to:
stack multiple biological cell images to form a multi-dimensional input tensor, the multiple biological cell images including biological cell images including different spectral bands of light, the multi-dimensional input tensor including at least a first dimension, a second dimension and a plurality of channels, wherein each of the different spectral bands of light is a channel C of the multi-dimensional input tensor, where parameters W and H of the multi-dimensional input tensor represent a width and a height of the biological cell images;
process the received multi-dimensional input tensor by passing the received multi-dimensional input tensor through the plurality of sequential encoder down-sampling blocks, the processing including a combination of cell segmentation and classification with multiple cell type annotation labels; and
generate an output tensor in response to processing the received multi-dimensional input tensor via the plurality of sequential encoder down-sampling blocks of the learning network, the output tensor including at least one segmentation classification.