WO2024037581A1 - 一种结膜充血的量化评估方法、装置和存储介质 - Google Patents

一种结膜充血的量化评估方法、装置和存储介质 Download PDF

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WO2024037581A1
WO2024037581A1 PCT/CN2023/113490 CN2023113490W WO2024037581A1 WO 2024037581 A1 WO2024037581 A1 WO 2024037581A1 CN 2023113490 W CN2023113490 W CN 2023113490W WO 2024037581 A1 WO2024037581 A1 WO 2024037581A1
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eye
conjunctival
channel value
image
conjunctival congestion
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PCT/CN2023/113490
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English (en)
French (fr)
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王卫庆
宁光
沈力韵
田超楠
杜东
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上海市内分泌代谢病研究所
上海佰翊医疗科技有限公司
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Publication of WO2024037581A1 publication Critical patent/WO2024037581A1/zh

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
    • A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
    • A61B3/107—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for determining the shape or measuring the curvature of the cornea
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
    • A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
    • A61B3/14—Arrangements specially adapted for eye photography

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  • the invention relates to the technical field of eye detection, and in particular to a quantitative assessment method, device and storage medium for conjunctival congestion.
  • the degree of conjunctival congestion is one of the important reference indicators for doctors to evaluate ocular inflammation in patients. Clinically, doctors are required to be within 1m of the patient and use manual experience to judge the degree of conjunctival congestion, whether it is mild, moderate or severe. Because of the subjective consciousness of different doctors, there is no unified standard for the judgment of mild, moderate and severe, which can easily lead to misdiagnosis or missed diagnosis.
  • the existing technology proposes a technical solution that uses shape-dependent image recognition.
  • an image including an eye captured by a camera is obtained, one or more blood vessels in the image are identified, and based on the identified The size of one or more blood vessels is used to determine the degree of conjunctival congestion.
  • the shape-dependent recognition method used in the existing technology has the following shortcomings: 1. It is easily affected by the color of blood vessels and cannot accurately extract red pixel values. , making the recognition inaccurate; 2. Due to the structural characteristics of the human eyeball, there will be a shadow at the junction of the eyelid and the eyeball, which affects the accuracy; 3. The same light beam shines on the eyeball, because the eyeball is a spherical surface, and uneven light will occur. .
  • the present invention proposes a quantitative assessment method for conjunctival congestion.
  • the present invention provides a quantitative assessment method for conjunctival congestion, which includes the following steps:
  • Step S1 Obtain a video of the eyeballs moving from inside to outside or from outside to inside;
  • Step S2 Perform eye image segmentation on the video to obtain an eye conjunctival image, and extract the red channel value and blue channel value of each pixel from the eye conjunctival image;
  • Step S3 Determine the percentage of conjunctival congestion through the ratio of the red channel value and the blue channel value of each pixel.
  • step S2 the second eye position map of the eyeball moving inward and outward to the extreme position is obtained respectively, and combined with the second eye position map of the eyeball moving inward to the extreme position and the eyeball moving outward.
  • the second eye position map to the extreme position obtains the eye conjunctival image.
  • the pixels whose ratio of the red channel value and the blue channel value exceed the threshold are red blood filaments, and the percentage of conjunctival congestion is that the area of the red blood filaments pixels accounts for the ocular conjunctival image. Percentage of conjunctival area.
  • the threshold is a fixed value set in advance, or the threshold is a manually set value.
  • the present application provides a device for quantitative assessment of conjunctival congestion, which device includes:
  • the video acquisition module is used to respond to video acquisition instructions and acquire videos of eyeballs moving from inside to outside or from outside to inside;
  • a feature extraction module configured to perform eye image segmentation on the video to obtain an eye conjunctival image, and extract the red channel value and blue channel value of each pixel from the eye conjunctival image;
  • the calculation module is used to calculate the ratio of the red channel value and the blue channel value of each pixel to determine the percentage of conjunctival congestion.
  • the feature extraction module also includes an image extraction module, configured to extract the second eye bitmap of the eyeball moving inward and outward to the extreme position from the video.
  • the present invention provides a computer-readable storage medium in which at least one program code is stored, and the at least one program code is loaded and executed by a processor to realize the first aspect of conjunctival hyperemia. quantitative assessment methods.
  • the present invention at least has the following beneficial effects:
  • the eye conjunctival image is synthesized through the second eye position map of the eyeball moving inward and outward to the extreme position, and then the red channel value and the blue channel value are extracted from each pixel of the image. Due to the light reflected by the bloodshot area Mainly red light, and the sclera itself has high reflectivity for both red and blue. Therefore, in places with bloodshot eyes, the red channel value is significantly higher than the blue channel value. In places without bloodshot eyes, the red channel value is significantly higher than the blue channel value. The color channel values are equivalent, and the congestion point can be accurately determined through the ratio of the red channel value and the blue channel value of each pixel, thereby determining the percentage of conjunctival congestion.
  • Figure 1 is a flow chart of the quantitative assessment method for conjunctival congestion provided by the present invention
  • Figure 2 is a functional block diagram of the quantitative assessment of conjunctival congestion provided by the present invention.
  • Figure 3 is a diagram illustrating the steps for quantitative assessment of conjunctival congestion provided by the present invention.
  • Figure 4 is a schematic structural diagram of a quantitative evaluation device for conjunctival congestion provided by the present invention.
  • a quantitative assessment method for conjunctival congestion includes the following steps:
  • Step S1 Obtain a video of the eyeballs moving from inside to outside or from outside to inside;
  • step S1 the user's eyes and head can be fixed through an eye evaluation or measurement device, and the horizontal movement of the eyeball from inside to outside or from outside to inside can be captured by a camera installed in front of the user's eye.
  • indicator lights can be used to indicate the movement of the user's eyeballs.
  • the required video of eye movements can also be obtained through other eye devices or video capture devices.
  • Step S2 Perform eye image segmentation on the video to obtain an eye conjunctival image, and extract the red channel value and blue channel value of each pixel from the eye conjunctival image;
  • step S2 the eye image segmentation of the video can be performed to obtain the eye conjunctival image without the eyeball.
  • the second eye bitmap of the eyeball moving inward and outward to the extreme position is extracted from the video, and then will extract The obtained second eye bitmap in which the eyeball moves inward to the extreme position and the second eye bitmap in which the eyeball moves outward to the extreme position are superimposed to obtain the eye conjunctival image, thereby obtaining the eye conjunctival image without the influence of the eyeball image, and then Extract the red channel value and blue channel value of each pixel from the eye conjunctival image.
  • eye position refers to the position of the eyeball during an eye examination, which is divided into first eye position, second eye position, and third eye position.
  • the first eye position refers to the eye position with both eyes looking straight ahead at infinity on the horizontal plane.
  • the second eye position refers to the eye position when the eyeballs rotate upward, downward, inward and outward.
  • the third eye position refers to the eyeballs pointing inward and upward. , the position of the eyes when turning obliquely from inside to bottom, outside to top, and outside to bottom, that is, the eye position when turning to the nose above, below the nose, above the temporal, and below the temporal.
  • the first, second, and third eye bitmaps respectively refer to images taken when the eyeball is in each eye position.
  • Step S3 Determine the percentage of conjunctival congestion through the ratio of the red channel value and the blue channel value of each pixel.
  • the percentage of conjunctival congestion is the ratio of the area of the red blood filaments pixels to the conjunctival area of the eye conjunctival image. percentage. Since the light reflected in the bloodshot area is mainly red light, and the sclera itself has a high reflectivity for both red and blue, the red channel value is significantly higher than the blue channel value in places with bloodshot eyes, while in places without bloodshot eyes , the red channel value and the blue channel value are equivalent, therefore, the percentage of conjunctival hyperemia is determined by the ratio of the red channel value and the blue channel value of each pixel.
  • the threshold is a fixed value set in advance, or the threshold is a manually set value. For example, you can enter a threshold value of 3 in the computer in advance, and determine that pixels with a ratio of red channel value to blue channel value exceeding 3 are red blood streaks. If the RGB value of a certain pixel is RGB (250, 245, 240), Then the red channel value is equal to the blue channel value, and the ratio between the two is close to 1. Then this pixel is not a red blood streak, but the white color of the sclera itself. If the RGB value of a certain pixel is RGB(250, 20, 15), Then the ratio of the red channel value to the blue channel value exceeds the threshold 3, and the pixel is determined to be a red blood filament. In addition to inputting the threshold value in advance, the threshold value can also be a value manually set by technicians such as doctors and operators based on experience.
  • Figure 3 shows the step diagram of the quantitative assessment method of conjunctival hyperemia in more detail.
  • the user controls the eyeballs to move left and right in front of the camera to record the video.
  • the next step is to perform eye image segmentation.
  • each image is obtained.
  • the second eye bitmap of the eyeball moving inward and outward to the extreme position is obtained by superimposing the second eye bitmap of the eyeball moving inward to the extreme position and the second eye bitmap of the eyeball moving outward to the extreme position.
  • Figure 4 is a schematic structural diagram 40 of a quantitative assessment device for conjunctival congestion provided by an embodiment of the present invention.
  • the device includes:
  • the video acquisition module 401 is used to respond to the video acquisition instruction and acquire a video of the eyeballs moving from inside to outside or from outside to inside.
  • the video acquisition module can control the camera or other shooting equipment to start, and guide the user's eye movement by controlling the voice device or lighting device to obtain the required eye movement. video.
  • the feature extraction module 402 is used to perform eye image segmentation on the video to obtain an eye conjunctival image, and extract the red channel value and blue channel value of each pixel from the eye conjunctival image.
  • the calculation module 403 is used to calculate the ratio of the red channel value and the blue channel value of each pixel, and determine the percentage of conjunctival congestion.
  • the feature extraction module also includes an image extraction module for extracting eyeballs from the video.
  • the second eye bitmap of moving inward and outward to the extreme position.
  • a computer-readable storage medium including a memory storing at least one program code, and the at least one program code is loaded and executed by the processor to complete the conjunctival hyperemia in the above embodiment.
  • Quantitative assessment methods can be read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), read-only compact disc (Compact Disc Read-Only Memory, CDROM), magnetic tape, Floppy disks and optical data storage devices, etc.
  • the storage medium can be a read-only memory, a magnetic disk or an optical disk, etc.

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Abstract

一种结膜充血的量化评估方法、装置和存储介质。结膜充血的量化评估方法包括以下步骤：步骤S1：获取眼球由内向外或者由外向内运动的视频；步骤S2：对视频进行眼部图像分割以获取眼部结膜图像，从眼部结膜图像中提取每一个像素的红色通道值和蓝色通道值；步骤S3：通过每一个像素的红色通道值和蓝色通道值的比值确定结膜充血的百分比。通过结膜充血的量化评估方法，能够得到结膜充血的精确值。

Description

一种结膜充血的量化评估方法、装置和存储介质 技术领域
本发明涉及眼部检测技术领域，具体涉及一种结膜充血的量化评估方法、装置和存储介质。
背景技术
结膜充血程度是医生在对患者眼部炎症进行评估时的重要参考指标之一。临床上医生要求距患者1m以内，以人工经验判断结膜轻、中、重的充血程度。因为不同医生的主观意识，关于轻、中、重的判断无统一标准，易造成误诊、漏诊。
针对人工测量存在准确度受人为因素影响的问题，现有技术提出了采用依赖形状的图像识别相关技术方案。如中国专利CN111212594A(申请号：CN201880066273.2，公开日：2020年05月29日)所述，获取由相机捕获的、包括眼睛的图像，识别图像中的一条或多条血管，并且基于所识别的一条或多条血管的尺寸来确定结膜充血程度。另外，现有技术中，还有一种利用眼部红色像素值所占的比例来检查结膜充血程度的方法，该方法具体通过获取高分辨率眼部图像，将眼部图像从RGB转换为灰白，利用高斯滤波找到横向与纵向梯度差别大的区域，在滤波热度图上利用阈值得出血丝与非血丝的分割。
但是眼部充血多为结膜充血，该区域充血多为弥散型，因此，现有技术中使用依赖形状的识别方法存在以下缺点：1、容易被血管颜色的深浅所影响，无法准确提取红色像素值，使识别不准确；2、由于人体眼球结构的特征，眼皮与眼球交接处会有阴影，影响准确度；3、同一光束照射在眼球上，因眼球是球面，会有光线不均匀的状况发生。
发明内容
为了克服现有技术在测量结膜充血程度方面的准确度不高的问题，本发明提出了一种结膜充血的量化评估方法。
为了实现上述目的，本发明采用以下技术方案：
一方面，本发明提供了一种结膜充血的量化评估方法，包括以下步骤：
步骤S1：获取眼球由内向外或者由外向内运动的视频；
步骤S2：对所述视频进行眼部图像分割以获取眼部结膜图像，从所述眼部结膜图像中提取每一个像素的红色通道值和蓝色通道值；
步骤S3：通过每一个像素的红色通道值和蓝色通道值的比值确定结膜充血的百分比。
进一步地，在所述步骤S2中，分别获取所述眼球向内、向外运动到极限位置的第二眼位图，结合眼球向内运动到极限位置的第二眼位图和眼球向外运动到极限位置的第二眼位图得到所述眼部结膜图像。
进一步地，在所述步骤S3中，判定红色通道值和蓝色通道值的比值超过阈值的像素点为红血丝，结膜充血的百分比为红血丝的像素点的面积占所述眼部结膜图像的结膜面积的百分比。
进一步地，所述阈值为提前设定的固定值，或者所述阈值为手动设置的值。
一方面，本申请提供了一种结膜充血的量化评估装置，所述装置包括：
视频获取模块，用于响应视频获取指令，获取眼球由内向外或者由外向内运动的视频；
特征提取模块，用于对所述视频进行眼部图像分割获取眼部结膜图像，并从所述眼部结膜图像中提取每一个像素的红色道值值和蓝色通道值；
计算模块，用于计算每一个像素的红色通道值和蓝色通道值的比值，确定结膜充血的百分比。
进一步的，所述特征提取模块，还包括图像提取模块，用于从所述视频中提取眼球向内、向外运动到极限位置的第二眼位图。
一方面，本发明提供了一种计算机可读存储介质，所述计算机可读存储介质中存储有至少一条程序代码，所述至少一条程序代码由处理器加载并执行以实现前述第一方面结膜充血的量化评估方法。
相较于现有技术，本发明至少具有以下有益效果：
本发明中通过眼球向内、向外运动到极限位置的第二眼位图合成眼部结膜图像，再从图像的每一像素中提取红色通道值和蓝色通道值，由于血丝区域反射的光以红光为主，而巩膜本身对于红和蓝皆有较高的反射率，因此在有血丝的地方，红色通道值显著高于蓝色通道值，而没有血丝的地方，红色通道值和蓝色通道值相当，通过每一像素红色通道值和蓝色通道值的比值可以准确地确定充血点，从而确定结膜充血的百分比。
附图说明
图1为本发明提供的结膜充血的量化评估方法流程图；
图2为本发明提供的结膜充血的量化评估原理框图；
图3为本发明提供的结膜充血的量化评估步骤图；
图4为本发明提供的结膜充血的量化评估装置结构示意图。
具体实施方式
下面结合附图和实施例，对本发明的具体实施方式作进一步详细描述。以下实施例用于说明本发明，但不用来限制本发明的范围。
如图1-3所示，一种结膜充血的量化评估方法，包括以下步骤：
步骤S1：获取眼球由内向外或者由外向内运动的视频；
具体的，在步骤S1中，可通过眼部评估或测量装置固定用户眼部、头部，通过设置于用户眼部前部的相机拍摄获取眼球由内向外或者由外向内作水平方向的移动的视频，可以采用指示灯指示用户眼球的运动。
也可以通过其他眼部设备或视频采集设备获取所需的眼球运动的视频。
步骤S2：对所述视频进行眼部图像分割以获取眼部结膜图像，从所述眼部结膜图像中提取每一个像素的红色通道值和蓝色通道值；
具体的，在步骤S2中，对视频进行眼部图像分割可以获得去除眼球的眼部结膜图像，具体通过从视频中分别提取眼球向内和向外运动到极限位置的第二眼位图，再将提取 到的眼球向内运动到极限位置的第二眼位图和眼球向外运动到极限位置的第二眼位图通过叠加得到眼部结膜图像，从而获取无眼球图像影响的眼部结膜图像，再从眼部结膜图像中提取每一个像素点的红色通道值和蓝色通道值。
需要说明的是，眼位是指在眼科检查中眼球的位置，分为第一眼位、第二眼位、第三眼位。第一眼位是指两眼在水平面上平视前方无限远处的眼位，第二眼位是指眼球向上、下、内、外转动时的眼位，第三眼位是指眼球向内上、内下、外上、外下作斜向转动时的眼位，即向鼻上、鼻下、颞上、颞下转动时的眼位。相应地，第一、第二、第三眼位图分别指眼球在各个眼位时拍摄的图像。
步骤S3：通过每一个像素的红色通道值和蓝色通道值的比值确定结膜充血的百分比。
在所述步骤S3中，判定红色通道值和蓝色通道值的比值超过阈值的像素点为红血丝，结膜充血的百分比为红血丝的像素点的面积占所述眼部结膜图像的结膜面积的百分比。由于血丝区域反射的光以红光为主，而巩膜本身对于红和蓝皆有较高的反射率，因此在有血丝的地方，红色通道值显著高于蓝色通道值，而没有血丝的地方，红色通道值和蓝色通道值相当，因此，通过每一个像素的红色通道值和蓝色通道值的比值确定结膜充血的百分比。具体地，所述阈值为提前设定的固定值，或者所述阈值为手动设置的值。例如，可以在计算机中提前输入阈值为3，判定红色通道值和蓝色通道值的比值超过3的像素点为红血丝，若某一像素点的RGB值为RGB(250，245，240)，则红色通道值和蓝色通道值相当，二者比值接近1，则此像素点不是红血丝，而是巩膜本身的白色，若某一像素点的RGB值为RGB(250，20，15)，则红色通道值与蓝色通道值的比值超过阈值3，判定此像素点为红血丝。除了提前输入阈值，所述阈值还可以是医生、操作者等技术人员根据经验手动设置的值。
图3更具体地示出了结膜充血的量化评估方法的步骤图，首先，用户在相机面前控制眼球左右移动，进行视频记录，下一步进行眼部图像分割，在眼部图像分割时，分别获取眼球向内、向外运动到极限位置的第二眼位图，通过将眼球向内运动到极限位置的第二眼位图和眼球向外运动到极限位置的第二眼位图叠加得到眼部结膜图像，再提取眼部结膜图像中每一个像素点的红色通道、蓝色通道值，进一步得到每一像素点的红蓝通道像素值的比值，并跟据提前设定的阈值或者手动设置的阈值判定每一个像素点是否为红血丝，从而得到红血丝的百分比。
图4是本发明实施例提供的一种结膜充血的量化评估装置的结构示意图40，参见图4，该装置包括：
视频获取模块401，用于响应视频获取指令，获取眼球由内向外或者由外向内运动的视频。在一种可能的实现方式中，视频获取模块在接收到获取指令时，可控制相机或其他拍摄设备启动，并通过控制语音设备或灯光装置，引导用户眼球运动，而获取所需的眼部运动视频。
特征提取模块402，用于对所述视频进行眼部图像分割获取眼部结膜图像，并从所述眼部结膜图像中提取每一个像素的红色道值和蓝色通道值。
计算模块403，用于计算每一个像素的红色通道值和蓝色通道值的比值，确定结膜充血的百分比。
进一步的，所述特征提取模块，还包括图像提取模块，用于从所述视频中提取眼球 向内、向外运动到极限位置的第二眼位图。
在示例性实施例中，还提供了一种计算机可读存储介质，包括存储有至少一条程序代码的存储器，所述至少一条程序代码由处理器加载并执行以完成上述实施例中的结膜充血的量化评估方法。例如，该计算机可读存储介质可以是只读存储器(Read-Only Memory,ROM)、随机存取存储器(Random Access Memory，RAM)、只读光盘(Compact Disc Read-Only Memory，CDROM)、磁带、软盘和光数据存储设备等。
本领域普通技术人员可以理解实现上述实施例的全部或部分步骤可以通过硬件来完成，也可以通过至少一条程序代码相关的硬件完成，该程序可以存储于一种计算机可读存储介质中，上述提到的存储介质可以是只读存储器，磁盘或光盘等。
以上所述仅为本发明的较佳实施例而已，并不用以限制本发明，凡在本发明的精神和原则之内所作的任何修改、等同替换和改进等，均应包含在本发明的保护范围之内。

Claims (7)

  1. 一种结膜充血的量化评估方法，其特征在于，包括以下步骤：
    步骤S1：获取眼球由内向外或者由外向内运动的视频；
    步骤S2：对所述视频进行眼部图像分割以获取眼部结膜图像，从所述眼部结膜图像中提取每一个像素的红色通道值和蓝色通道值；
    步骤S3：通过每一个像素的红色通道值和蓝色通道值的比值确定结膜充血的百分比。
  2. 根据权利要求1所述的结膜充血的量化评估方法，其特征在于：在所述步骤S2中，分别获取所述眼球向内、向外运动到极限位置的第二眼位图，结合眼球向内运动到极限位置的第二眼位图和眼球向外运动到极限位置的第二眼位图得到所述眼部结膜图像。
  3. 根据权利要求1所述的结膜充血的量化评估方法，其特征在于：在所述步骤S3中，判定红色通道值和蓝色通道值的比值超过阈值的像素点为红血丝，结膜充血的百分比为红血丝的像素点的面积占所述眼部结膜图像的结膜面积的百分比。
  4. 根据权利要求3所述的结膜充血的量化评估方法，其特征在于：所述阈值为提前设定的固定值，或者所述阈值为手动设置的值。
  5. 一种结膜充血的量化评估装置，其特征在于，所述装置包括：
    视频获取模块，用于响应视频获取指令，获取眼球由内向外或者由外向内运动的视频；
    特征提取模块，用于对所述视频进行眼部图像分割获取眼部结膜图像，并从所述眼部结膜图像中提取每一个像素的红色道值值和蓝色通道值；
    计算模块，用于计算每一个像素的红色通道值和蓝色通道值的比值，确定结膜充血的百分比。
  6. 根据权利要求5所述的结膜充血的量化评估装置，其特征在于，所述特征提取模块，还包括：
    图像处理子模块，用于从所述视频中提取眼球向内、向外运动到极限位置的第二眼位图，结合眼球向内运动到极限位置的第二眼位图和眼球向外运动到极限位置的第二眼位图得到所述眼部结膜图像。
  7. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质中存储有至少一条程序代码，所述至少一条程序代码由处理器加载并执行如权利要求1-4任一项所述的结膜充血的量化评估方法。
PCT/CN2023/113490 2022-08-18 2023-08-17 一种结膜充血的量化评估方法、装置和存储介质 WO2024037581A1 (zh)

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