303results about How to "Reduce misdiagnosis rate" patented technology

The invention discloses a deep convolutional neural network-based lung cancer preventing self-service health cloud service system. The system comprises a convolutional neural network used for deep learning and training identification, a segmentation module which segments out a lung region from a CT image based on a full convolutional neural network, a deep convolutional neural network used for lung cancer diagnosis classification, and a self-service health cloud service platform used for performing early prevention and treatment according to an identified suspected lung cancer type. According to the system, the automation and intelligentization level of mobile internet-based lung cancer screening can be effectively improved, more citizens can know and participate in self-service health detection, assessment and guidance, the sensitivity, specificity and accuracy of early lung cancer screening and clinical diagnosis are improved, the lung cancer can be early discovered, early diagnosed and early treated, and the self-health management capability is enhanced.

The invention provides an image processing method and device based on a pathological tissue section image organization area. The image processing method based on the pathological tissue section image organization area comprises the steps: step 1, pre-processing a pathological tissue section image to obtain a sub image block; step 2, extracting sub image block characteristics on the basis of a deep convolutional neural network model, integrating the sub image block characteristics to obtain pathological tissue section image characteristics and pre-classifying the pathological tissue section image characteristics to obtain an abnormal pathological tissue section image; step 3, quantifying clinical hospital visiting information; step 5, using a multi-source data fusion technology to obtain fusion characteristics according to abnormal pathological tissue section image characteristics and the clinical hospital visiting information; and step 5, classifying the fusion characteristics by using a classifier. The image processing device based on the pathological tissue section image organization area comprises a pre-processing module, a characteristic extracting module, a classification module, a quantization module and a data fusion module. The image processing method and device based on the pathological tissue section image organization area, provided by the invention, have the advantage that a problem of poor organization area detection effect of the pathological tissue section image in the prior art is overcome.