Fetal ultrasound image recognition method and system based on deep learning
The invention discloses a fetal ultrasonic image recognition method and system based on deep learning. The method comprises the steps that ultrasonic equipment detects and sends fetal ultrasonic parameter information to a data terminal according to a printing operation control instruction; the data...
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| creator | WANG NAN LIANG ZHE XIE HONGNING XIAN JIANBO MAO MINGCHUN |
| description | The invention discloses a fetal ultrasonic image recognition method and system based on deep learning. The method comprises the steps that ultrasonic equipment detects and sends fetal ultrasonic parameter information to a data terminal according to a printing operation control instruction; the data terminal receives and sends the ultrasonic parameter information to a cloud server; the cloud serverreceives the ultrasonic static image and performs segmentation operation on the ultrasonic static image based on a predetermined image segmentation model to obtain segmented sub-images, and inputs the segmented sub-images into a predetermined image classification model to obtain a classification model result; the cloud server sends the classification model result to the main control device; and the main control equipment receives and outputs the classification model result. According to the invention, deep learning can be applied to examination of the fetal ultrasound image, so that the identification efficiency and |
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The method comprises the steps that ultrasonic equipment detects and sends fetal ultrasonic parameter information to a data terminal according to a printing operation control instruction; the data terminal receives and sends the ultrasonic parameter information to a cloud server; the cloud serverreceives the ultrasonic static image and performs segmentation operation on the ultrasonic static image based on a predetermined image segmentation model to obtain segmented sub-images, and inputs the segmented sub-images into a predetermined image classification model to obtain a classification model result; the cloud server sends the classification model result to the main control device; and the main control equipment receives and outputs the classification model result. 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The method comprises the steps that ultrasonic equipment detects and sends fetal ultrasonic parameter information to a data terminal according to a printing operation control instruction; the data terminal receives and sends the ultrasonic parameter information to a cloud server; the cloud serverreceives the ultrasonic static image and performs segmentation operation on the ultrasonic static image based on a predetermined image segmentation model to obtain segmented sub-images, and inputs the segmented sub-images into a predetermined image classification model to obtain a classification model result; the cloud server sends the classification model result to the main control device; and the main control equipment receives and outputs the classification model result. 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The method comprises the steps that ultrasonic equipment detects and sends fetal ultrasonic parameter information to a data terminal according to a printing operation control instruction; the data terminal receives and sends the ultrasonic parameter information to a cloud server; the cloud serverreceives the ultrasonic static image and performs segmentation operation on the ultrasonic static image based on a predetermined image segmentation model to obtain segmented sub-images, and inputs the segmented sub-images into a predetermined image classification model to obtain a classification model result; the cloud server sends the classification model result to the main control device; and the main control equipment receives and outputs the classification model result. According to the invention, deep learning can be applied to examination of the fetal ultrasound image, so that the identification efficiency and</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTING COUNTING HANDLING RECORD CARRIERS HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA IMAGE DATA PROCESSING OR GENERATION, IN GENERAL INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS |
| title | Fetal ultrasound image recognition method and system based on deep learning |
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