技术领域technical field
本发明涉及冠脉医学图像处理技术领域，特别涉及一种基于分析线提取的血管钙化区域检测方法。The invention relates to the technical field of coronary medical image processing, in particular to a method for detecting a vascular calcification region based on analysis line extraction.
背景技术Background technique
自动化冠脉医学图像检测对医生而言具有重要的临床价值和实际意义，其能够能为医生反馈直观的检测结果，从而作为医生进行病情诊断的参考，将医生从解读医学图像的繁琐工作中解脱出来，从而降低了医生的诊断时间，提高诊断效率，缓解当前就医难的问题。Automated coronary medical image detection has important clinical value and practical significance for doctors. It can feedback intuitive detection results for doctors, so as to serve as a reference for doctors to diagnose diseases, and relieve doctors from the tedious work of interpreting medical images. It can reduce the diagnosis time of doctors, improve the efficiency of diagnosis, and alleviate the current problem of difficult medical treatment.
钙化区域识别是自动化冠脉医学图像检测中的重要一环，钙化一般在医学图像上的表现形式通常是其亮度值高于周围血管的亮度值，据此，现有的算法很多是利用动态阈值进行区分，进而识别出钙化区域。对于块状钙化区域，检测效果良好，但对于钙化有很长一段的情况，动态阈值方式就难以获得准确的检出结果。The identification of calcified regions is an important part of automatic coronary medical image detection. The general manifestation of calcification in medical images is that its brightness value is higher than that of surrounding blood vessels. According to this, many existing algorithms use dynamic thresholds. Differentiation is performed to identify calcified areas. For massive calcified areas, the detection effect is good, but for long-term calcifications, dynamic threshold method is difficult to obtain accurate detection results.
发明内容SUMMARY OF THE INVENTION
为解决上述问题，本发明提供了一种基于分析线提取的血管钙化区域检测方法。In order to solve the above problems, the present invention provides a method for detecting a vascular calcification region based on analysis line extraction.
本发明采用以下技术方案：The present invention adopts the following technical solutions:
一种基于分析线提取的血管钙化区域检测方法，包括以下步骤：A vascular calcification region detection method based on analysis line extraction, comprising the following steps:
S1、获取血管拉直图像，并进行分割处理获得血管区域图像；S1, obtaining a blood vessel straightening image, and performing segmentation processing to obtain a blood vessel region image;
S2、针对血管区域图像，统计垂直血管方向的灰度值均值，并生成一维灰度值曲线；S2. For the image of the blood vessel area, count the mean value of the gray value in the vertical blood vessel direction, and generate a one-dimensional gray value curve;
S3、统计所述一维灰度值曲线沿血管方向的灰度值均值，生成阈值曲线；S3. Count the mean value of the gray value of the one-dimensional gray value curve along the blood vessel direction to generate a threshold curve;
S4、基于阈值曲线，将所述一维灰度值曲线上的区域划分为暗区和亮区，对所述暗区、亮区分别进行极小值选取、极大值选取，生成新的一维灰度值曲线；S4, based on the threshold curve, divide the area on the one-dimensional gray value curve into a dark area and a bright area, and select a minimum value and a maximum value for the dark area and the bright area, respectively, to generate a new one dimensional gray value curve;
S5、通过对新的一维灰度值曲线进行大窗口平滑，探测出突变区域作为钙化候选区域。S5. By performing large window smoothing on the new one-dimensional gray value curve, a mutation region is detected as a calcification candidate region.
优选地，所示步骤S3具体通过以下方法实现：Preferably, the shown step S3 is specifically realized by the following method:
将一维灰度值曲线沿血管方向分成前段和后段，分别统计前段和后段的灰度值均值，然后通过拟合生成所述阈值曲线。The one-dimensional gray value curve is divided into an anterior segment and a posterior segment along the blood vessel direction, the average gray value of the anterior segment and the posterior segment is counted, and then the threshold curve is generated by fitting.
优选地，所述步骤S4通过以下方法实现：Preferably, the step S4 is realized by the following method:
对所述一维灰度值曲线做修改，将一维灰度值曲线某位置的值记为a，将阈值曲线上对应位置的值记为b,若a+预设阈值>b，则判定该位置属于所述亮区上的位置并取该位置在血管区域图像上垂直血管方向的极大值替换a，若a<b,则判定该位置属于所述暗区上的位置并取该位置在血管区域图像上垂直血管方向的极小值替换a，最终生成新的一维灰度值曲线。Modify the one-dimensional gray value curve, denote the value of a certain position on the one-dimensional gray value curve as a, and denote the value of the corresponding position on the threshold curve as b, if a+preset threshold>b, then determine the The position belongs to the position on the described bright area and takes the maximum value of the position in the vertical blood vessel direction on the image of the blood vessel area to replace a, if a<b, then determine that the position belongs to the position on the dark area and take the position at The minimum value of the vertical blood vessel direction on the blood vessel area image replaces a, and finally a new one-dimensional gray value curve is generated.
优选地，所述步骤S5通过以下分步骤实现：Preferably, the step S5 is realized by the following sub-steps:
S51、通过对新的一维灰度值曲线进行大窗口平滑，生成平滑曲线；S51, generating a smooth curve by performing large-window smoothing on the new one-dimensional gray value curve;
S52、将新的一维灰度值曲线与平滑曲线进行比对，探测出突变区域为钙化位置；S52, compare the new one-dimensional gray value curve with the smooth curve, and detect that the mutation area is the calcification position;
S53、输出所述钙化位置，并将所述血管区域图像上的对应位置作为钙化候选区域。S53. Output the calcification position, and use the corresponding position on the blood vessel region image as a calcification candidate region.
一种基于分析线提取的血管钙化区域检测系统，包括获取模块、一维曲线生成模块、阈值曲线生成模块、一维曲线调整模块及突变区域探测模块，所述获取模块用于获取血管拉直图像并进行分割处理获得血管区域图像，所述一维曲线生成模块用于统计垂直血管方向的灰度值均值并生成一维灰度值曲线，所述阈值曲线生成模块用于统计沿血管方向的灰度值均值并生成阈值曲线，所述一维曲线调整模块用于将一维灰度值曲线上的区域划分为暗区和亮区，对所述暗区、亮区分别进行极小值、极大值选取和替换，生成新的一维灰度值曲线，所述突变区域探测模块通过大窗口平滑探测新的一维灰度值曲线上的突变区域作为钙化候选区域。A blood vessel calcification region detection system based on analysis line extraction, comprising an acquisition module, a one-dimensional curve generation module, a threshold curve generation module, a one-dimensional curve adjustment module and a mutation region detection module, the acquisition module is used for acquiring blood vessel straightening images And perform segmentation processing to obtain a blood vessel area image, the one-dimensional curve generation module is used to count the mean value of the gray value in the vertical blood vessel direction and generate a one-dimensional gray value curve, and the threshold curve generation module is used to count the gray value along the blood vessel direction. The mean value of the intensity value and the threshold curve are generated. The one-dimensional curve adjustment module is used to divide the area on the one-dimensional gray value curve into a dark area and a bright area. The large value is selected and replaced to generate a new one-dimensional gray value curve, and the mutation region detection module smoothly detects the mutation region on the new one-dimensional gray value curve through a large window as a calcification candidate region.
优选地，所述突变区域探测模块包括大窗口平滑子模块、比对子模块及转换子模块，所述大窗口平滑子模块用于通过对新的一维灰度值曲线进行大窗口平滑并生成平滑曲线，所述比对子模块用于将新的一维灰度值曲线与平滑曲线进行比对，探测出突变区域为钙化位置，所述转换子模块用于输出所述钙化位置并将所述血管区域图像上的对应位置作为钙化候选区域。Preferably, the mutation region detection module includes a large-window smoothing sub-module, a comparison sub-module and a conversion sub-module, and the large-window smoothing sub-module is used to perform large-window smoothing on the new one-dimensional gray value curve and generate Smooth curve, the comparison sub-module is used to compare the new one-dimensional gray value curve with the smooth curve, and detects that the mutation region is a calcification position, and the conversion sub-module is used to output the calcification position and convert all the calcification positions. The corresponding position on the blood vessel region image is used as the calcification candidate region.
采用上述技术方案后，本发明与背景技术相比，具有如下优点：After adopting the above-mentioned technical scheme, the present invention has the following advantages compared with the background technology:
本发明根据血管图像转换为一维灰度值曲线进行分析，利用阈值曲线划分出暗区和亮区，做极小值、极大值选取，然后通过大窗口平滑，探测出曲线上的突变区域作为钙化候选区域。本发明能够有效检测出血管图像上的长段状钙化区域，有效避免了漏检情况的发生。The invention converts the blood vessel image into a one-dimensional gray value curve for analysis, uses the threshold curve to divide the dark area and the bright area, selects the minimum value and the maximum value, and then smoothes through a large window to detect the mutation area on the curve as calcification candidate regions. The invention can effectively detect the long-segment calcified area on the blood vessel image, and effectively avoid the occurrence of missed detection.
附图说明Description of drawings
图1为本发明的流程示意图。FIG. 1 is a schematic flow chart of the present invention.
具体实施方式Detailed ways
为了使本发明的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本发明进行进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.
实施例一Example 1
参考图1所示，本发明公开了一种基于分析线提取的血管钙化区域检测方法，包括以下步骤：Referring to Fig. 1, the present invention discloses a method for detecting vascular calcification region based on analysis line extraction, which includes the following steps:
S1、获取血管拉直图像，并进行分割处理获得血管区域图像。S1. Obtain a blood vessel straightening image, and perform segmentation processing to obtain a blood vessel region image.
S2、针对血管区域图像，统计垂直血管方向的灰度值均值，并生成一维灰度值曲线。S2. For the image of the blood vessel area, count the mean value of the gray value in the direction of the vertical blood vessel, and generate a one-dimensional gray value curve.
S3、统计一维灰度值曲线沿血管方向的灰度值均值，生成阈值曲线。在本实施例中，阈值曲线的生成方式具体为：将一维灰度值曲线沿血管方向分成前段和后段，分别统计前段和后段的灰度值均值，然后通过拟合生成阈值曲线。S3. Count the mean value of the gray value of the one-dimensional gray value curve along the blood vessel direction to generate a threshold curve. In this embodiment, the method for generating the threshold curve is as follows: divide the one-dimensional gray value curve into an anterior segment and a posterior segment along the blood vessel direction, count the average gray value of the anterior segment and posterior segment respectively, and then generate the threshold curve by fitting.
S4、基于阈值曲线，将一维灰度值曲线上的区域划分为暗区和亮区，对暗区、亮区分别进行极小值选取、极大值选取，生成新的一维灰度值曲线。该步骤通过以下方法实现：对一维灰度值曲线做修改，将一维灰度值曲线某位置的值记为a，将阈值曲线上对应位置的值记为b,若a+预设阈值>b，则判定该位置属于亮区上的位置并取该位置在血管区域图像上垂直血管方向的极大值替换a，若a<b,则判定该位置属于暗区上的位置并取该位置在血管区域图像上垂直血管方向的极小值替换a，最终生成新的一维灰度值曲线。S4. Based on the threshold curve, divide the area on the one-dimensional gray value curve into a dark area and a bright area, select the minimum value and the maximum value for the dark area and the bright area, respectively, to generate a new one-dimensional gray value curve. This step is realized by the following methods: modifying the one-dimensional gray value curve, denoting the value of a certain position of the one-dimensional gray value curve as a, and denoting the value of the corresponding position on the threshold curve as b, if a+preset threshold> b, then determine that the position belongs to the position on the bright area and take the maximum value of the position in the vertical blood vessel direction on the image of the blood vessel area to replace a, if a<b, then determine that the position belongs to the position on the dark area and take the position Replace a with the minimum value in the vertical direction of the blood vessel on the image of the blood vessel area, and finally generate a new one-dimensional gray value curve.
S5、通过对新的一维灰度值曲线进行大窗口平滑，探测出突变区域作为钙化候选区域。该步骤通过以下分步骤实现：S5. By performing large window smoothing on the new one-dimensional gray value curve, a mutation region is detected as a calcification candidate region. This step is achieved in the following sub-steps:
S51、通过对新的一维灰度值曲线进行大窗口平滑，生成平滑曲线。S51 , generating a smooth curve by performing large-window smoothing on the new one-dimensional gray value curve.
S52、将新的一维灰度值曲线与平滑曲线进行比对，探测出突变区域为钙化位置。具体来说，对于某个位置，若其在新的一维灰度值曲线与平滑曲线的存在大的差异，且该位置在新的一维灰度值曲线的值a大于其在阈值曲线上的值b与预设阈值之和，则该位置为钙化位置。S52. Compare the new one-dimensional gray value curve with the smooth curve, and detect that the mutation region is a calcification position. Specifically, for a certain position, if there is a large difference between the new one-dimensional gray value curve and the smooth curve, and the value a of the position on the new one-dimensional gray value curve is greater than that on the threshold curve The sum of the value b of , and the preset threshold, the position is the calcification position.
S53、输出钙化位置，并将血管区域图像上的对应位置作为钙化候选区域。S53, output the calcification position, and use the corresponding position on the blood vessel region image as the calcification candidate region.
实施例二Embodiment 2
一种基于分析线提取的血管钙化区域检测系统，包括获取模块、一维曲线生成模块、阈值曲线生成模块、一维曲线调整模块及突变区域探测模块，其中:A vascular calcification region detection system based on analysis line extraction, comprising an acquisition module, a one-dimensional curve generation module, a threshold curve generation module, a one-dimensional curve adjustment module and a mutation region detection module, wherein:
获取模块用于获取血管拉直图像并进行分割处理获得血管区域图像。The acquisition module is used to acquire the blood vessel straightening image and perform segmentation processing to obtain the blood vessel region image.
一维曲线生成模块用于统计垂直血管方向的灰度值均值并生成一维灰度值曲线。The one-dimensional curve generation module is used to count the mean value of the gray value in the vertical blood vessel direction and generate a one-dimensional gray value curve.
阈值曲线生成模块用于统计沿血管方向的灰度值均值并生成阈值曲线。The threshold curve generation module is used to count the mean value of gray values along the blood vessel direction and generate a threshold curve.
一维曲线调整模块用于将一维灰度值曲线上的区域划分为暗区和亮区，对暗区、亮区分别进行极小值、极大值选取和替换，生成新的一维灰度值曲线。The one-dimensional curve adjustment module is used to divide the area on the one-dimensional gray value curve into a dark area and a bright area, and select and replace the minimum and maximum values of the dark area and the bright area, respectively, to generate a new one-dimensional gray value. Degree curve.
突变区域探测模块通过大窗口平滑探测新的一维灰度值曲线上的突变区域作为钙化候选区域。突变区域探测模块包括大窗口平滑子模块、比对子模块及转换子模块，大窗口平滑子模块用于通过对新的一维灰度值曲线进行大窗口平滑并生成平滑曲线，比对子模块用于将新的一维灰度值曲线与平滑曲线进行比对，探测出突变区域为钙化位置，转换子模块用于输出钙化位置并将血管区域图像上的对应位置作为钙化候选区域。The mutation region detection module smoothly detects the mutation region on the new one-dimensional gray value curve as a calcification candidate region through a large window. The mutation region detection module includes a large-window smoothing sub-module, a comparison sub-module and a conversion sub-module. The large-window smoothing sub-module is used to perform large-window smoothing on the new one-dimensional gray value curve and generate a smooth curve, and the comparison sub-module It is used to compare the new one-dimensional gray value curve with the smooth curve, and detect the mutation area as the calcification position. The conversion sub-module is used to output the calcification position and use the corresponding position on the blood vessel area image as the calcification candidate area.
以上所述，仅为本发明较佳的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到的变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应该以权利要求的保护范围为准。The above description is only a preferred embodiment of the present invention, but the protection scope of the present invention is not limited to this. Substitutions should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.
| Application Number | Priority Date | Filing Date | Title |
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| CN201910256885.4ACN110033442B (en) | 2019-04-01 | 2019-04-01 | Vascular calcification area detection method and system based on analysis line extraction |
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| CN201910256885.4ACN110033442B (en) | 2019-04-01 | 2019-04-01 | Vascular calcification area detection method and system based on analysis line extraction |
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| CN110033442Atrue CN110033442A (en) | 2019-07-19 |
| CN110033442B CN110033442B (en) | 2020-12-25 |
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| CN201910256885.4AActiveCN110033442B (en) | 2019-04-01 | 2019-04-01 | Vascular calcification area detection method and system based on analysis line extraction |
| Country | Link |
|---|---|
| CN (1) | CN110033442B (en) |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080119734A1 (en)* | 2006-11-22 | 2008-05-22 | Celine Pruvot | Method, system, and computer product for automatically extracting and tracking cardiac calcifications and determining a tracking centerline |
| US20120075638A1 (en)* | 2010-08-02 | 2012-03-29 | Case Western Reserve University | Segmentation and quantification for intravascular optical coherence tomography images |
| CN105380682A (en)* | 2015-12-24 | 2016-03-09 | 飞依诺科技(苏州)有限公司 | Bilateral intima-media membrane measuring method and system based on ultrasonic images |
| CN106372654A (en)* | 2016-08-29 | 2017-02-01 | 滕忠照 | Method for assessing cerebral infarction risk caused by head and neck atherosclerosis plaques |
| CN108171698A (en)* | 2018-02-12 | 2018-06-15 | 数坤（北京）网络科技有限公司 | A kind of method of automatic detection human heart Coronary Calcification patch |
| CN108257196A (en)* | 2018-01-11 | 2018-07-06 | 苏州润心医疗器械有限公司 | A kind of blood vessel based on cardiac CT image stretches method for reconstructing |
| CN108765363A (en)* | 2018-03-24 | 2018-11-06 | 语坤（北京）网络科技有限公司 | A kind of automatic after-treatment systems of coronary artery CTA based on artificial intelligence |
| CN108805815A (en)* | 2018-06-14 | 2018-11-13 | 苏州润迈德医疗科技有限公司 | Blood vessel based on X-ray angiographic image stretches method for reconstructing |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080119734A1 (en)* | 2006-11-22 | 2008-05-22 | Celine Pruvot | Method, system, and computer product for automatically extracting and tracking cardiac calcifications and determining a tracking centerline |
| US20120075638A1 (en)* | 2010-08-02 | 2012-03-29 | Case Western Reserve University | Segmentation and quantification for intravascular optical coherence tomography images |
| CN105380682A (en)* | 2015-12-24 | 2016-03-09 | 飞依诺科技(苏州)有限公司 | Bilateral intima-media membrane measuring method and system based on ultrasonic images |
| CN106372654A (en)* | 2016-08-29 | 2017-02-01 | 滕忠照 | Method for assessing cerebral infarction risk caused by head and neck atherosclerosis plaques |
| CN108257196A (en)* | 2018-01-11 | 2018-07-06 | 苏州润心医疗器械有限公司 | A kind of blood vessel based on cardiac CT image stretches method for reconstructing |
| CN108171698A (en)* | 2018-02-12 | 2018-06-15 | 数坤（北京）网络科技有限公司 | A kind of method of automatic detection human heart Coronary Calcification patch |
| CN108765363A (en)* | 2018-03-24 | 2018-11-06 | 语坤（北京）网络科技有限公司 | A kind of automatic after-treatment systems of coronary artery CTA based on artificial intelligence |
| CN108805815A (en)* | 2018-06-14 | 2018-11-13 | 苏州润迈德医疗科技有限公司 | Blood vessel based on X-ray angiographic image stretches method for reconstructing |
| Title |
|---|
| 张新生 等: "乳腺图像微钙化簇主动学习检测新方法", 《西安电子科技大学学报（自然科学版）》* |
| 蔡甫雨: "基于DSA和CTA影像的冠状动脉血流动力学仿真分析", 《中国优秀硕士学位论文全文数据库 医药卫生科技辑》* |
| Publication number | Publication date |
|---|---|
| CN110033442B (en) | 2020-12-25 |
| Publication | Publication Date | Title |
|---|---|---|
| CN107480677B (en) | Method and device for identifying interest region in three-dimensional CT image | |
| JP4149598B2 (en) | Method for automatically setting collimator of X-ray imaging system during image acquisition, and X-ray imaging system | |
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| JP7355434B2 (en) | Fundus image recognition method, device, and equipment | |
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