Liver hemodynamic detection device based on multiple hepatic vein oscillograms

Abstract

The invention provides a liver hemodynamic detection device based on multiple hepatic vein oscillograms, and the device comprises: an image obtaining module which is used for obtaining a hepatic vein detection image and a portal vein detection image uploaded by a client; the waveform boundary determining module that is used for determining a waveform boundary; the waveform recognition module that is used for cutting the hepatic vein detection picture and the portal vein detection picture, and determining an upper waveform or a lower waveform of the oscillogram by taking the condition that the average gray value of pixel points of each straight line is lower than a threshold value as a judgment standard; the frequency shift calculation module that is used for determining the frequency shift of the oscillogram in each hepatic vein detection picture relative to the oscillogram in the portal vein detection picture in the upper waveform or the lower waveform; the frequency shift calibration module that is used for calculating a frequency shift calibration value based on the preset proportion of each hepatic vein; and the hepatic fibrosis degree determination module that is used for determining the hepatic fibrosis degree according to the frequency shift calibration value and a preset hepatic fibrosis index comparison table.

Description

technical field [0001] The present application belongs to the technical field of data processing, and in particular relates to a liver hemodynamic detection device based on multiple hepatic vein waveform diagrams. Background technique [0002] Liver fibrosis is caused by chronic damage to the liver, including hepatitis B and C, alcoholic liver disease, nonalcoholic fatty liver disease (NAFLD), and autoimmune hepatitis. As liver fibrosis progresses, excessive accumulation of extracellular matrix proteins leads to increased liver stiffness, leading to cirrhosis, liver failure, and liver cancer. [0003] The established gold standard for detecting liver fibrosis uses an invasive needle biopsy and relies on visual inspection of tissue images by a pathologist. Problems with needle biopsy include: 1) low accuracy due to large sampling errors and variability in interpretation by pathologists; 2) pain and potential medical risks (eg, massive bleeding) associated with invasive proce...

AI Technical Summary

Problems solved by technology

Problems with needle biopsy include: 1) low accuracy due to large sampling errors and variability in interpretation by pathologists; 2) pain and potential medical risks associated with invasive procedures (eg, major bleeding)

There also exists a non-invasive technique which is a comparison of various frequency patterns from different veins in the liver (portal, left hepatic, middle hepatic, and right hepatic veins) by mapping frequency shifts with hepatic fibrosis indices The degree of hepatic fibrosis can be judged by the relationship between them. Since the special frequency detection equipment is used, the frequency images of multiple veins output by the special frequency detection equipment may easily cause technical defects that the medical staff cannot accurately identify and accurately determine the degree of liver fibrosis.

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