Convolutional neural network classification of pretreatment biopsies
AssigneeWashington University
InventorsMichael Waters, Jin Zhang, Hyun Kim
Life of this patent
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Abstract
A method and apparatus are provided for pretreatment prediction system comprising display device a computing device comprising a processor and a memory, the memory storing instructions that, when executed by the processor cause the processor to receive at least one image of a pre-treatment biopsy from a patient process the at least one image using a trained convolutional neural network (CNN) display on the display device, a prediction of a response of the patient to a treatment base on a result of the processing of the at least one image using the trained CNN.
Claims20
A pretreatment prediction system comprising:
- a display device;
- a computing device comprising a processor and a memory, the memory storing instructions that, when executed by the processor, cause the processor to:
- receive at least one image of a pre-treatment biopsy from a patient;
- process the at least one image using a trained convolutional neural network (CNN);
- display, on the display device, a prediction of a response of the patient to a treatment base on a result of the processing of the at least one image using the trained CNN.
A method of predicting a treatment outcome, the method comprising:
- receiving at least one image of a pre-treatment biopsy from a patient;
- processing the at least one image using a trained convolutional neural network (CNN);
- and
- displaying, on a display device, a prediction of a response of the patient to a treatment base on a result of the processing of the at least one image using the trained CNN.
A computer readable storage medium comprising instructions that when executed by a processor cause the processor to:
- receive at least one image of a pre-treatment biopsy from a patient;
- process the at least one image using a trained convolutional neural network (CNN);
- and
- display, on a display device, a prediction of a response of the patient to a treatment base on a result of the processing of the at least one image using the trained CNN.
Dependencies are inferred from the claim text.