CN108242055B - Myocardial fusion image processing method and system - Google Patents
Myocardial fusion image processing method and system Download PDFInfo
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Abstract
The invention provides a myocardial fusion image processing method and a system, wherein the method comprises the following steps: step S1: marking all coronary artery stenosis areas causing myocardial ischemia on the SPECT/CT fusion image, and marking myocardial ischemia areas; step S2: inputting corresponding prompt information in the coronary artery stenosis region or the myocardial ischemia region, and displaying the prompt information when a cursor hovers over the coronary artery stenosis region or the myocardial ischemia region of the fused image; step S3: collecting and judging the rule of myocardial ischemia in the coronary artery stenosis region on the SPECT/CT fusion image, and collecting and judging the rule of coronary artery stenosis in the coronary artery stenosis region; step S4: and analyzing the myocardial ischemia condition of the SPECT/CT fusion image according to the learned rule. The invention reduces the error of myocardial ischemia image analysis and provides reference for myocardial ischemia detection.
Description
Technical Field
The invention relates to the technical field of medical image processing, in particular to a method and a system for processing an image based on myocardial fusion.
Background
With the development of medical technology, medical imaging technology has been increasingly applied to practical medical research and treatment. Single-Photon Emission Computed Tomography (SPECT), a CT technique of nuclear medicine, is commonly referred to as Emission Computed Tomography because it images gamma rays emitted from a patient. However, because the imaging of SPECT is not clear enough, single SPECT imaging is gradually replaced by SPECT/CT, which has become one of the most advanced medical imaging devices at present and is an ideal tool for diagnosing living diseases and researching and developing new drugs.
SPECT/CT fused images can provide more information and guidelines for diagnosis of myocardial disease and determine whether a stenting procedure is required. For example, from SPECT/CT fused images, it is easy to find whether a stenotic coronary artery causes myocardial ischemia; for example, by using the SPECT/CT fusion image, the relationship between myocardial ischemia diseases and coronary heart diseases can be found, and the accurate judgment of the reasons of myocardial ischemia is the key to the treatment of the coronary heart diseases and the heart diseases.
In order to obtain more accurate myocardial ischemia information, doctors usually need to analyze SPECT images or SPECT/CT fusion images, but the SPECT images are easy to show false positive phenomena of false ischemia due to superimposed instability, so that misdiagnosis is easily caused in clinical diagnosis. Analysis of SPECT/CT fusion images is also quite difficult because the relationship between coronary artery disease and myocardial ischemia is complex: coronary stenosis is not equal to myocardial ischemia, and myocardial ischemia is not equal to coronary stenosis. When the coronary artery is narrowed, the doctor cannot easily find the reason causing myocardial ischemia; when a plurality of stenoses occur in one coronary artery, it is difficult to judge which one is the cause of myocardial ischemia; when the relation between the coronary artery and the myocardial mass is abnormally changed, the relation is difficult to be found by a doctor; in myocardial ischemia, coronary arteries are normal, and the cause of myocardial ischemia is difficult to find.
Disclosure of Invention
The invention aims to provide a myocardial fusion image processing method and a myocardial fusion image processing system, which can automatically analyze the existence condition of myocardial ischemia for a SPECT/CT fusion image according to the rule, thereby reducing the misjudgment of myocardial ischemia false positive image analysis, reducing the error of myocardial ischemia image analysis and providing image data for myocardial ischemia detection.
In order to achieve the above object, the present invention provides a method for processing a myocardial fusion image, comprising the following steps:
step S1: marking all coronary artery stenosis areas causing myocardial ischemia on the SPECT/CT fusion image, and marking myocardial ischemia areas;
step S2: inputting corresponding prompt information in the coronary artery stenosis region or the myocardial ischemia region, and displaying the prompt information when a cursor hovers over the coronary artery stenosis region or the myocardial ischemia region of the fused image;
step S3: collecting and judging the rule of myocardial ischemia in the coronary artery stenosis region on the SPECT/CT fusion image according to the prompt information, and collecting and judging the rule of coronary artery stenosis in the coronary artery stenosis region;
step S4: and performing machine learning on the rule, and analyzing the myocardial ischemia condition of the SPECT/CT fusion image according to the learned rule.
Further, in the myocardial fusion image processing method described above, the step S3 further includes:
the step of collecting and judging the rule of myocardial ischemia in the coronary artery stenosis region on the SPECT/CT fusion image according to the prompt information specifically comprises the following steps:
judging whether myocardial ischemia exists in the coronary artery stenosis region according to the prompt information,
if yes, highlighting a myocardial ischemia part in a coronary artery stenosis region of the fusion image;
if not, the myocardial ischemia site is not displayed in the coronary artery stenosis region of the fusion image.
Further, in the myocardial fusion image processing method, the step of collecting, on the SPECT/CT fusion image according to the prompt information, a rule for determining that myocardial ischemia exists in the coronary artery stenosis region further includes:
judging whether coronary artery stenosis exists in the myocardial ischemia area or not according to the prompt information,
if yes, highlighting the coronary artery stenosis part in the myocardial ischemia area of the fusion image;
if not, the coronary artery stenosis region is not displayed in the myocardial ischemia region of the fusion image.
In addition, the present invention provides a system for analyzing a myocardial fusion image, including:
a marking unit for marking all coronary artery stenosis areas causing myocardial ischemia on the SPECT/CT fusion image and marking myocardial ischemia areas;
the input display unit is used for inputting corresponding prompt information in the coronary artery stenosis area or the myocardial ischemia area, and displaying the prompt information when a cursor hovers over the coronary artery stenosis area or the myocardial ischemia area of the fusion image;
the rule collecting unit is used for collecting and judging the rule of myocardial ischemia in the coronary artery stenosis region and the rule of coronary artery stenosis in the myocardial ischemia region on the SPECT/CT fusion image according to the prompt information;
and the learning judgment unit is used for performing machine learning on the rule and analyzing the myocardial ischemia condition of the SPECT/CT fusion image according to the learned rule.
Further, in the system for analyzing a myocardial fusion image, the rule collecting unit is further configured to determine whether myocardial ischemia exists in the coronary artery stenosis region according to the prompt information, and if so, highlight a myocardial ischemia site in the coronary artery stenosis region of the fusion image; if not, the myocardial ischemia site is not displayed in the coronary artery stenosis region of the fusion image.
Further, in the analysis system of the myocardial fusion image, the rule collecting unit is further configured to determine whether there is coronary artery stenosis in the myocardial ischemia area according to the prompt information, and if so, highlight a coronary artery stenosis portion in the myocardial ischemia area of the fusion image; if not, the coronary artery stenosis region is not displayed in the myocardial ischemia region of the fusion image.
The myocardial fusion image processing method and the myocardial fusion image processing system judge whether myocardial ischemia exists or not through summarizing and learning, and can automatically analyze the existence condition of myocardial ischemia on the SPECT/CT fusion image according to the rule, thereby reducing the error of myocardial ischemia image analysis and providing reference for myocardial ischemia detection.
Drawings
Fig. 1 is a flowchart illustrating a myocardial fusion image processing method according to the present invention.
Fig. 2 is a schematic flow chart illustrating the process of fig. 1 for determining the existence of myocardial ischemia in the coronary artery stenosis region.
Fig. 3 is another schematic flow chart of fig. 1 for determining the existence of myocardial ischemia in the coronary artery stenosis region.
Fig. 4a is a bull's eye diagram based on a conventional myocardial fusion image.
Fig. 4b is a bull's eye diagram based on a myocardium fusion image according to the present invention.
FIG. 5 is a schematic representation of a labeled myocardial fusion based image of the present invention.
FIG. 6 is a diagram illustrating an analysis system of a myocardial fusion image according to the present invention.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
Referring to fig. 1, fig. 1 is a flowchart illustrating a myocardial fusion image processing method according to the present invention. The method comprises the following steps:
step S1: marking all coronary artery stenosis areas causing myocardial ischemia on the SPECT/CT fusion image, and marking myocardial ischemia areas;
in the concrete implementation, firstly, a nuclide physical attenuation correction step: aiming at SPECT/CT equipment provided with a multi-pinhole quasi-master device, calculating a nuclide attenuation correction coefficient of each dynamic time point by an exponential decay module (exponential decay module) according to the starting time point and the acquisition time length of dynamic SPECT acquisition and the half-life of 99 Union Tc nuclide, and re-correcting radioactivity count which is required to be possessed in an original projection image; then, acquiring a SPECT/CT fusion image through a CT blood flow perfusion image; finally, all coronary artery stenosis regions causing myocardial ischemia are marked on the fusion image through CT localization, and myocardial ischemia regions are marked.
Step S2: inputting corresponding prompt information in the coronary artery stenosis region or the myocardial ischemia region, and displaying the prompt information when a cursor hovers over the coronary artery stenosis region or the myocardial ischemia region of the fused image;
when the cursor is hovered in an ischemic region or a coronary artery stenosis region, additional prompt information is described; the prompt information depends on the specific situation of the hovering position. In this example, the myocardial ischemic region is shown in bluish purple, and the deeper the degree of ischemia, the darker the color; and the coronary stenosis region may be displayed in another distinguishable color, such as a deep red color.
Step S3: and collecting and judging the rule of the myocardial ischemia in the coronary artery stenosis region on the SPECT/CT fusion image according to the prompt information, and collecting and judging the rule of the coronary artery stenosis in the coronary artery ischemia region.
In the concrete implementation, the rule that whether myocardial ischemia exists is judged by a doctor on the SPECT/CT fusion image according to the prompt information.
Step S4: and performing machine learning on the rule, and analyzing the myocardial ischemia condition of the SPECT/CT fusion image according to the learned rule.
In the concrete implementation, machine learning is carried out according to the rule of a series of collected conditions matched with the coronary artery stenosis and the multiple groups of myocardial ischemia, so that the existence probability of myocardial ischemia is judged for the SPECT/CT fusion image according to the learned rule.
Therefore, the rule of judging whether myocardial ischemia exists or not is summarized and learned, and the existence condition of myocardial ischemia can be automatically analyzed on the SPECT/CT fusion image according to the rule, so that the error of myocardial ischemia image analysis is reduced, and image data are provided for myocardial ischemia detection.
Referring to fig. 2, fig. 2 is a schematic flow chart illustrating a procedure for determining the existence of myocardial ischemia in the coronary artery stenosis region in fig. 1. The step of collecting and judging the rule of myocardial ischemia in the coronary artery stenosis region on the SPECT/CT fusion image according to the prompt information specifically comprises the following steps:
step 101: judging whether myocardial ischemia exists in the coronary artery stenosis region according to the prompt information, if so, entering step 102; if not, go to step 103;
step 102: the myocardial ischemia site is highlighted in the coronary artery stenosis region of the fused image.
Step 103: the coronary artery stenosis region in the fusion image does not show a myocardial ischemia site.
In specific implementation, whether myocardial ischemia exists in the coronary artery stenosis region or not is judged according to the prompt information, if yes, the fact that the myocardial ischemia occurs in the coronary artery stenosis region is shown, and the information of the degree of coronary artery stenosis is displayed on the fusion image, and the information can help a doctor to check the reason of the myocardial ischemia (possibly corresponding coronary artery stenosis); if not, the fact that the coronary artery stenosis occurs in the coronary artery stenosis region but the ischemic myocardium is not found is described, and the doctor can obtain the information through the prompt information and the fusion image.
Referring to fig. 3, fig. 3 is another schematic flow chart of fig. 1 for determining the existence of myocardial ischemia in the coronary artery stenosis region. The step of collecting and judging the rule of myocardial ischemia in the coronary artery stenosis region on the SPECT/CT fusion image according to the prompt information further comprises the following steps:
step 104: judging whether coronary artery stenosis exists in the myocardial ischemia area or not according to the prompt information, and if so, entering step 105; if not, go to step 106;
step 105: highlighting a coronary stenosis in a myocardial ischemic region of the fused image;
step 106: the myocardial ischemic region in the fused image does not show a coronary artery stenosis portion.
In concrete implementation, whether coronary artery stenosis exists in the myocardial ischemia area or not is judged according to the prompt information, if yes, the myocardial ischemia area is indicated to have corresponding or other coronary artery stenosis, and the coronary artery stenosis part is highlighted on the fusion image and possibly is a cause of myocardial ischemia. From this information, the physician can filter out other useless fused image information; if not, the myocardial ischemia area is determined to have no corresponding or other coronary artery stenosis, that is, the area has no obvious coronary artery marker, but the myocardial ischemia area is obvious, and the information helps the doctor to eliminate other reasons, such as myocardial ischemia caused by coronary artery stenosis.
Please refer to fig. 4a and 4b, which are bull's eye diagrams based on myocardial fusion images of the prior art and the present invention, respectively. The bull's eye plot is an analysis of myocardial and coronary involvement by dividing the left ventricle into 17 segments. And (3) numerical calculation: the left and right are quantitative evaluation results of ischemia and stenosis, respectively. In fig. 4a, the conventional method directly calculates quantitative data of drug concentration according to time compensation and background compensation, and further calculates data that can be referred by a doctor, but the conventional method is inaccurate due to shooting skills, uneven drug distribution and the like. The improved method of the present invention in fig. 4b corrects the above calculation results by recording the judgment results of the doctor to achieve more accurate quantitative information, as shown in fig. 4b, the degree of ischemia of the lower apical region is found by the method of the present invention, and has correlation with quantitative assessment of stenosis.
Referring to fig. 5, fig. 5 is a schematic diagram of a labeled myocardial fusion-based image according to the present invention. As can be seen from fig. 5, there is no coronary stenosis at the myocardial ischemia site, and there is no myocardial ischemia at the coronary stenosis site.
In addition, referring to fig. 6, the present invention further provides a system for analyzing a myocardial fusion image, including: a marking unit 10 for marking all coronary artery stenosis regions causing myocardial ischemia on the received SPECT/CT fusion image and marking myocardial ischemia regions; an entry display unit 20, configured to enter corresponding prompt information in the coronary artery stenosis region or the myocardial ischemia region, and display the prompt information when a cursor hovers over the coronary artery stenosis region or the myocardial ischemia region of the fused image; the rule collecting unit 30 is used for collecting and judging a rule that the coronary artery stenosis region has myocardial ischemia and a rule that the coronary artery stenosis region has coronary artery stenosis on the SPECT/CT fusion image according to the prompt information; and the learning judgment unit 40 is used for performing machine learning on the rule and analyzing the myocardial ischemia condition of the SPECT/CT fusion image according to the learned rule.
The rule collecting unit 30 is further configured to determine whether myocardial ischemia exists in the coronary artery stenosis region according to the prompt information, and if so, highlight a myocardial ischemia part in the coronary artery stenosis region of the fused image; if not, the myocardial ischemia site is not displayed in the coronary artery stenosis region of the fusion image.
The rule collecting unit 30 is further configured to determine whether coronary artery stenosis exists in the myocardial ischemia area according to the prompt information, and if so, highlight a coronary artery stenosis portion in the myocardial ischemia area of the fusion image; if not, the coronary artery stenosis region is not displayed in the myocardial ischemia region of the fusion image.
Compared with the prior art, the myocardial fusion image processing method and the myocardial fusion image processing system judge whether myocardial ischemia exists or not through summarizing and learning, and can automatically analyze the existence condition of myocardial ischemia on the SPECT/CT fusion image according to the rule, so that the error of myocardial ischemia image analysis is reduced, and image data are provided for myocardial ischemia detection.
The description and applications of the invention herein are illustrative and are not intended to limit the scope of the invention to the embodiments described above. Variations and modifications of the embodiments disclosed herein are possible, and alternative and equivalent various components of the embodiments will be apparent to those skilled in the art. It will be clear to those skilled in the art that the present invention may be embodied in other forms, structures, arrangements, proportions, and with other components, materials, and parts, without departing from the spirit or essential characteristics thereof. Other variations and modifications of the embodiments disclosed herein may be made without departing from the scope and spirit of the invention.
Claims (2)
1. A myocardial fusion image processing method is characterized by comprising the following steps:
step S1: marking all coronary artery stenosis areas causing myocardial ischemia on the SPECT/CT fusion image, and marking myocardial ischemia areas;
step S2: inputting corresponding prompt information in the coronary artery stenosis region or the myocardial ischemia region, and displaying the prompt information when a cursor hovers over the coronary artery stenosis region or the myocardial ischemia region of the fused image;
step S3: collecting and judging the rule of myocardial ischemia in the coronary artery stenosis region on the SPECT/CT fusion image according to the prompt information, and collecting and judging the rule of coronary artery stenosis in the coronary artery stenosis region;
step S4: performing machine learning on the rule, and analyzing the myocardial ischemia condition of the SPECT/CT fusion image according to the learned rule;
the step S3 further includes:
the step of collecting and judging the rule of myocardial ischemia in the coronary artery stenosis region on the SPECT/CT fusion image according to the prompt information specifically comprises the following steps:
judging whether myocardial ischemia exists in the coronary artery stenosis region according to the prompt information,
if yes, highlighting a myocardial ischemia part in a coronary artery stenosis region of the fusion image;
if not, the myocardial ischemia part is not displayed in the coronary artery stenosis region of the fusion image;
the step of collecting and judging the rule of myocardial ischemia in the coronary artery stenosis region on the SPECT/CT fusion image according to the prompt information further comprises the following steps:
judging whether coronary artery stenosis exists in the myocardial ischemia area or not according to the prompt information,
if yes, highlighting the coronary artery stenosis part in the myocardial ischemia area of the fusion image;
if not, the coronary artery stenosis region is not displayed in the myocardial ischemia region of the fusion image.
2. A system for analyzing a myocardial fusion image, comprising:
a marking unit for marking all coronary artery stenosis areas causing myocardial ischemia on the SPECT/CT fusion image and marking myocardial ischemia areas;
the input display unit is used for inputting corresponding prompt information in the coronary artery stenosis area or the myocardial ischemia area, and displaying the prompt information when a cursor hovers over the coronary artery stenosis area or the myocardial ischemia area of the fusion image;
the rule collecting unit is used for collecting and judging the rule that the coronary artery stenosis region has myocardial ischemia and the rule that the coronary artery stenosis region has coronary artery stenosis on the SPECT/CT fusion image according to the prompt information;
the learning judgment unit is used for performing machine learning on the rule and analyzing the myocardial ischemia condition of the SPECT/CT fusion image according to the learned rule;
the rule collecting unit is further used for judging whether myocardial ischemia exists in the coronary artery stenosis region according to the prompt information, and if yes, the myocardial ischemia position is highlighted in the coronary artery stenosis region of the fusion image; if not, the myocardial ischemia part is not displayed in the coronary artery stenosis region of the fusion image;
the rule collecting unit is further used for judging whether coronary artery stenosis exists in the myocardial ischemia area or not according to the prompt information, and if yes, highlighting the coronary artery stenosis part in the myocardial ischemia area of the fusion image; if not, the coronary artery stenosis region is not displayed in the myocardial ischemia region of the fusion image.
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| CN104582572A (en) * | 2012-08-16 | 2015-04-29 | 株式会社东芝 | Image-processing device, diagnostic medical image apparatus and blood pressure monitor |
| CN104783826A (en) * | 2015-03-20 | 2015-07-22 | 常州市第一人民医院 | Myocardial perfusion development and coronary artery calcification score combined diagnostic system and method |
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| CN104783826A (en) * | 2015-03-20 | 2015-07-22 | 常州市第一人民医院 | Myocardial perfusion development and coronary artery calcification score combined diagnostic system and method |
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