Fatty liver intelligent grading evaluation method based on abdominal CT

Abstract

The invention relates to a fatty liver intelligent grading evaluation method based on abdominal CT, and relates to the field of intelligent medical image diagnosis. The method comprises the followingsteps: reading an abdominal CT image of a patient, selecting nearby four layers of slices corresponding to the maximum area of liver and spleen to construct a training sample set, and carrying out thepreprocessing of the data of the training sample set; constructing a UNet segmentation network model, sending the training sample to the segmentation network model for supervised learning, and aftertraining convergence of the segmentation model, using the model to segment CT slices to segment liver tissues and spleen tissues in the slices; respectively carrying out gridding cutting on liver tissues and spleen tissues to obtain a plurality of small rectangular areas with the same area, randomly selecting five small rectangular areas in the two tissues as sampling areas, calculating respectivegray average values as a liver CT value and a spleen CT value, and finally grading the fatty liver according to a liver / spleen CT ratio. According to the method, full-automatic segmentation of the liver tissue and the spleen tissue based on the abdominal CT image is realized, so that the fatty liver is intelligently graded and evaluated.

Description

technical field [0001] The invention relates to the field of intelligent medical image diagnosis, in particular to an intelligent grading and evaluation method for fatty liver based on abdominal CT. Background technique [0002] Today's human diet structure and activity patterns have undergone tremendous changes. A well-off life allows people to obtain excess fat in their diet, but physical labor is much reduced, which indirectly induces many diseases of affluence. Fatty liver, as a relatively common digestive system disease, is caused by abnormal fat metabolism in liver cells due to various reasons, resulting in excessive accumulation of fat. Early diagnosis and timely treatment of fatty liver can often return to normal. Clinically, B-ultrasound, CT and other imaging techniques are often used for qualitative and quantitative diagnosis of fatty liver. Due to the accumulation of fat in CT examination, fatty liver is mainly manifested as a decrease in liver density. In imagin...

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Problems solved by technology

Manual segmentation of CT images is time-consuming and labor-intensive, and then a semi-automatic segmentation method appeared, but it is also necessary to give the initial segmentation curve of the organ on the CT image in order to realize the segmentation of the organ

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