Hypertension risk prediction method based on traditional Chinese medicine theory and palm multi-feature extraction

A technology for risk prediction and hypertension, applied in the field of medical image processing, which can solve the problems of cumbersome and inconvenient detection

Pending Publication Date: 2020-11-17
SHANXI HUIHU HEALTH TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] At present, the detection of high blood pressure needs to go to hospitals and other medical institutions for special testing, which is cumbersome and inconvenient

Method used

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  • Hypertension risk prediction method based on traditional Chinese medicine theory and palm multi-feature extraction
  • Hypertension risk prediction method based on traditional Chinese medicine theory and palm multi-feature extraction
  • Hypertension risk prediction method based on traditional Chinese medicine theory and palm multi-feature extraction

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0087] figure 1 It is a schematic flowchart of a hypertension risk prediction method based on TCM theory and palm multi-feature extraction provided by Embodiment 1 of the present invention; figure 2 It is a schematic structural diagram of the key point model of the hand in Embodiment 1 of the present invention; figure 1 , figure 2 As shown, a hypertension risk prediction method based on TCM theory and palm multi-feature extraction includes:

[0088] S10, acquiring an image of the palm to be tested;

[0089] S20, establishing a key point model of the hand; the key point model of the hand includes: position information of main joints of the hand;

[0090] S30, performing corresponding ROI segmentation on the image information according to the features of the lifeline crossing the midline, the ruddy feature, the uplift feature, and the hypertrophy feature;

[0091] S40, detect the lifeline crossing the midline ROI region corresponding to the lifeline crossing the midline fe...

Embodiment 2

[0119] Figure 8 It is a schematic flow diagram of detecting the lifeline crossing the midline ROI region corresponding to the lifeline crossing the midline feature in the second embodiment; as Figure 8 As shown, on the basis of Embodiment 1, a hypertension risk prediction method based on TCM theory and palm multi-feature extraction, the step S40 is to detect the lifeline crossing midline ROI region corresponding to the lifeline crossing midline feature, and based on Edge detection algorithm and curve fitting algorithm judge whether the lifeline crosses the midline, if the lifeline intersects the midline, calculate the weight Weight 1 , otherwise the weight is 0, including:

[0120] S401. Perform grayscale processing on the image in the ROI region where the lifeline crosses the midline, and convert it into a grayscale image; the conversion formula is: Gray=(R*30+G*59+B*11+50) / 100.

[0121] S402, after obtaining the gradient in the x direction through the Scharr operator, us...

Embodiment 3

[0154] Figure 11 It is a schematic flow diagram of performing ruddy detection on the ruddy ROI region corresponding to the ruddy feature in the third embodiment; Figure 12 It is the effect diagram of color area extraction in the third embodiment; as Figure 11 , Figure 12 As shown, on the basis of Embodiment 1, a method for predicting the risk of hypertension based on TCM theory and palm multi-feature extraction, the step S50, the rosy ROI area corresponding to the ruddy feature is ruddy detection, by HSV-based The color gamut space judges whether it is ruddy, and if it is ruddy, the weight of ruddy is Weight 2 , otherwise the weight is 0, including:

[0155] S501, convert the acquired image into HSV color space; HSV can more intuitively observe the hue, vividness and lightness of the color, so it performs better in color contrast, and it is easier to track objects of a certain color, which can be used to segment specific Color object; the calculation formula of RGB to ...

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Abstract

The invention provides a hypertension risk prediction method based on a traditional Chinese medicine theory and palm multi-feature extraction. The method comprises the steps of obtaining an image of ato-be-detected palm; establishing a hand key point model; respectively carrying out corresponding ROI segmentation on the image information according to the lifeline midline passing feature, the ruddy feature, the upheaval feature and the hypertrophy feature; detecting a lifeline passing-through-center-line ROI region corresponding to the lifeline passing-through-center-line feature to judge whether a lifeline passes through a center line; performing ruddy detection on the ruddy ROI corresponding to the ruddy features to judge whether the ROI is ruddy; performing hypertrophy and upheaval detection on the hypertrophy ROI region corresponding to the hypertrophy feature and the upheaval ROI region corresponding to the upheaval feature, and judging whether the regions are hypertrophy and upheaval; judging whether a hypertension risk exists or not through the midline weight Weight1, the ruddy weight Weight2, the hypertrophy weight Weight3 and the heave weight Weight4; the method has the beneficial effects of being capable of quickly identifying palmprint information and enabling people to perform self-test on hypertension, and is suitable for the field of medical image processing.

Description

technical field [0001] The invention relates to the technical field of medical image processing, in particular to a method for predicting the risk of hypertension based on traditional Chinese medicine theory and palm multi-feature extraction. Background technique [0002] In TCM theory, hand diagnosis refers to an auxiliary method of prevention and treatment that can be used to reason about the evolution of human organs through the pattern, change, and regularity of the lines of the human hand. As early as the Tang Dynasty, Wang Chao recorded the case of inferring the disease based on the observation of the color and shape of the superficial vein on the inner side of the index finger in the "Shui Jing Tu Jue". Dodd's "Aristotle Palmistry" has had a profound impact on later generations. [0003] The palm print is an important window to reflect the health status of the human body. Studying the palm print can help us understand the internal development of the body; there are a...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/32G06K9/62G06T5/30G06T7/00G06T7/11G06T7/13G06T7/136G06T7/90G16H50/30
CPCG06T5/30G06T7/0012G06T7/11G06T7/13G06T7/136G06T7/90G16H50/30G06T2207/10024G06T2207/20081G06V40/13G06V40/1347G06V10/25G06F18/214G06F18/253
Inventor 王华虎杨星宇冀伦文强彦李慧芝赵紫娟
Owner SHANXI HUIHU HEALTH TECH CO LTD
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