Croho disease and intestinal tuberculosis classification method based on multi-sequence MRI images
The invention discloses a Croho disease and intestinal tuberculosis classification method based on multi-sequence MRI images, and the method comprises the steps: obtaining a plurality of abdominal cavity MRI images carrying intestinal tissue regions of a same target object, inputting the plurality o...
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| creator | LU BAOLAN ZHANG NAIWEN LIN HAIWEI FANG ZHUANGNIAN FENG SHITING HUANG BINGSHENG ZENG YINGHOU LI XUEHUA LIU JIAWEI ZHANG MENGCHEN MENG JIXIN YUAN CHENGLANG |
| description | The invention discloses a Croho disease and intestinal tuberculosis classification method based on multi-sequence MRI images, and the method comprises the steps: obtaining a plurality of abdominal cavity MRI images carrying intestinal tissue regions of a same target object, inputting the plurality of abdominal cavity MRI images into a trained classification network model, and determining that the focus type of the target object is a Crow disease type or an intestinal tuberculosis type through the classification network model. According to the invention, the trained classification network model is used to learn the abdominal cavity MRI image carrying the omnibearing features of the intestinal tract lesion, and a large amount of lesion feature information of the Crow's disease CD and the intestinal tuberculosis ITB can be excavated, so that the lesion category of the target object can be accurately determined as the Crow's disease category or the intestinal tuberculosis category. Further, the accuracy of identi |
| format | Patent |
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According to the invention, the trained classification network model is used to learn the abdominal cavity MRI image carrying the omnibearing features of the intestinal tract lesion, and a large amount of lesion feature information of the Crow's disease CD and the intestinal tuberculosis ITB can be excavated, so that the lesion category of the target object can be accurately determined as the Crow's disease category or the intestinal tuberculosis category. 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According to the invention, the trained classification network model is used to learn the abdominal cavity MRI image carrying the omnibearing features of the intestinal tract lesion, and a large amount of lesion feature information of the Crow's disease CD and the intestinal tuberculosis ITB can be excavated, so that the lesion category of the target object can be accurately determined as the Crow's disease category or the intestinal tuberculosis category. 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According to the invention, the trained classification network model is used to learn the abdominal cavity MRI image carrying the omnibearing features of the intestinal tract lesion, and a large amount of lesion feature information of the Crow's disease CD and the intestinal tuberculosis ITB can be excavated, so that the lesion category of the target object can be accurately determined as the Crow's disease category or the intestinal tuberculosis category. Further, the accuracy of identi</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING HANDLING RECORD CARRIERS IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS |
| title | Croho disease and intestinal tuberculosis classification method based on multi-sequence MRI images |
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