A method for estimating the optimal phase of cardiac reconstruction

Abstract

The present invention discloses a method for estimating the best phase for cardiac reconstruction. When implemented, the method is operated according to the following steps: performing a cardiac scan to obtain ECG information; calculating the best phase according to the ECG information; and reconstructing an image using the best phase. The method of the present invention uses the standard deviation of the signal to estimate the amplitude of the signal fluctuation, and uses the probability of the best phase occurring at different phases to adjust the best phase, automatically calculating the best phase, and having high calculation accuracy.

Description

Technical Field

[0001] The present invention relates to the field of medical imaging technology, and more particularly to a method for estimating an optimal phase for cardiac reconstruction. Background Art

[0002] Phase is a key parameter in the reconstruction of cardiac CT data. Choosing the correct phase can minimize motion artifacts in the image and achieve the best image quality. However, traditionally, in the process of cardiac reconstruction, the best phase is determined by the distribution of ECG signals, and the amplitude of signal fluctuation is obtained by querying the maximum and minimum values ​​of the signal within a time interval. This method is easily affected by noise in the signal and has a low accuracy rate. Doctors need to manually reconstruct data at different phases and select images with fewer motion artifacts from all results. This process takes a lot of time and effort, so a method is needed to automatically calculate the best phase. Summary of the invention

[0003] In view of the shortcomings of the prior art, the present invention provides a method for estimating the optimal phase of cardiac reconstruction, which uses the standard deviation of the signal to estimate the signal fluctuation amplitude, and uses the probability of the optimal phase occurring in different phases to adjust the optimal phase, with high calculation accuracy.

[0004] To achieve the above object, the present invention provides the following technical solution: a method for estimating the optimal phase of cardiac reconstruction, comprising the following steps:

[0005] (i) obtaining ECG signals of heart scans;

[0006] (ii) Starting from the phase 2% or other initial phase, a phase sequence is generated with a smaller phase interval (such as 2%), and a phase is taken out from the phase sequence in turn as the current phase, which is recorded as phase p i , where i∈[1, N], N is the number of phases in the sequence, and the first and last timestamps of the current phase window in each heartbeat cycle are calculated according to the preset phase width, and the ECG signal within the range of the first and last timestamps is marked;

[0007] (III) Take out the phase p i The corresponding marked ECG signals are used to calculate the standard deviation of these signals, denoted as σ i ;

[0008] (IV) In general, the best phase is often concentrated around 70%. Based on the large amount of clinical data collected in practice, the probability of each phase in the phase sequence being the best phase can be given, denoted as g i ;

[0009] (V) Calculate the signal standard deviation σ at different phases iWith probability g i The best phase index:

[0010]

[0011]

[0012] (VI) Combination signal standard deviation σ i With probability g i The best phase index, z i =α×z σ，i +(1-α)×z g,i Where α is a weight adjustment factor so that z i The smallest phase is the optimal phase.

[0013] Furthermore, in step (iv), these large amounts of data may be classified, such as classified according to heart rate, to improve accuracy.

[0014] When looking for the best phase, we need to find the phase with the smallest heart movement amplitude, but the ECG signal is essentially an electrical signal generated by the heart. There is a phase difference between the ECG signal cycle and the heart movement cycle, such as Figure 2 shown. Figure 1 The medium gray background is the most common optimal phase, namely the end of systole (left) and the end of diastole (right). Searching for the optimal phase simply through ECG signals often results in large deviations, such as Figure 2 In order to find the best phase more accurately, it is necessary to make another adjustment after finding the phase corresponding to the point where the ECG signal changes the least over time.

[0015] In summary, the present invention uses the standard deviation of the signal to estimate the signal fluctuation amplitude, and uses the probability of the best phase occurring in different phases to adjust the best phase, and automatically calculates the best phase with high calculation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a typical schematic diagram of the changes of ventricular volume and ECG signal in one heart cycle;

[0017] Figure 2 The best phase is calculated simply by using ECG signals, which is ideally shown in the left figure, but inaccurate results often occur, as shown in the right figure;

[0018] Figure 3 The left figure shows the standard deviation σ of the signal i The right figure is a schematic diagram of the distribution of the probability of the best phase at any time;

[0019] Figure 4is the optimal phase index z i Distribution curve. DETAILED DESCRIPTION

[0020] Reference Figures 1 to 4 A specific implementation of a method for estimating the optimal phase of cardiac reconstruction according to the present invention is further described.

[0021] Below Figure 2 The inaccurate results in the example are used to illustrate the specific processing process of the present invention:

[0022] The first step is to obtain the ECG signal of the heart scan.

[0023] The second step is to generate a phase sequence starting from phase 2% (or other initial phase) with a smaller phase interval (such as 2%). One phase is taken out from the phase sequence in turn as the current phase, which is recorded as phase p i , where i∈[1, N], N is the number of phases in the sequence. The first and last timestamps of the current phase window in each heartbeat cycle are calculated according to the preset phase width, and the ECG signal within the range of the first and last timestamps is marked.

[0024] The third step is to extract the phase p i The corresponding marked ECG signals are used to calculate the standard deviation of these signals, denoted as σ i ,like Figure 3 As shown in the left picture.

[0025] Step 4: Generally speaking, the best phase is often concentrated around 70%. Based on the large amount of clinical data collected in practice, the probability of each phase in the phase sequence being the best phase can be given, denoted as g i ,like Figure 2 As shown in the right figure. This figure is just an example. After using a large amount of data, it can more accurately reflect the actual situation. (At the same time, as an optimization option, these large amounts of data can be classified to improve accuracy. For example, classification according to heart rate.)

[0026]

[0027]

[0028] Step 6: Combine the signal standard deviation σ i With probability g i The best phase index, z i =α×z σ，i +(1-α)×z g，i Where α is a weight adjustment factor so that z i The smallest phase is the best phase, such as Figure 4 The image was reconstructed using the optimal phase.

[0029] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A method for estimating the optimal phase of cardiac reconstruction, characterized in that: The following steps are included: (a) Obtaining ECG signals for heart scans; (ii) Starting from the phase 2% or other initial phase, a phase sequence is generated with a smaller phase interval, and a phase is taken out from the phase sequence in turn as the current phase, which is recorded as phase ,in , is the number of phases in the sequence. The start and end timestamps of the current phase window in each heartbeat cycle are calculated according to the preset phase width, and the ECG signal within the range of the start and end timestamps is marked. (III) Removal of phase The corresponding marked ECG signals are calculated and the standard deviation of these signals is recorded as ; (IV) In general, the best phase is concentrated around 70%. Based on a large amount of clinical data collected in practice, the probability of each phase in the phase sequence being the best phase is given, denoted as ; 5. Calculate the standard deviation of signals at different phases With probability The best phase index: ； ； 6. Combination signal standard deviation With probability The best phase index, ; in is a weight adjustment factor such that The smallest phase is the optimal phase.

2. The method for estimating the optimal phase of cardiac reconstruction according to claim 1, characterized in that: In the step (iv), these large amounts of data are classified and processed.

3. The method for estimating the optimal phase of cardiac reconstruction according to claim 2, characterized in that: The classification processing method includes classification according to high and low heart rates to improve accuracy.

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