Matplotlib 简明教程

Matplotlib - MRI with EEG

MRI 与 EEG 指的是将两种不同的方法结合在一起用于研究大脑的医学成像技术：核磁共振成像 (MRI) 和脑电图 (EEG)。

MRI with EEG refers to a medical imaging technique that combines two different methods to study the brain: Magnetic Resonance Imaging (MRI) and Electroencephalography (EEG).

MRI (Magnetic Resonance Imaging) - MRI 使用强磁场和无线电波来创建身体内部（包括大脑）的详细图像。它帮助医生了解大脑的结构和解剖，检测肿瘤、损伤或其他疾病等异常情况。

MRI (Magnetic Resonance Imaging) − MRI uses strong magnetic fields and radio waves to create detailed images of the inside of the body, including the brain. It helps doctors see the structure and anatomy of the brain, detecting abnormalities like tumors, injuries, or other conditions.

EEG (Electroencephalography) - EEG 通过在头皮上放置电极来测量大脑中的电活动。它记录了由称为神经元的脑细胞产生的电脉冲模式。

EEG (Electroencephalography) − EEG measures the electrical activity in the brain by placing electrodes on the scalp. It records the patterns of electrical impulses produced by brain cells, called neurons.

将 MRI 和 EEG 结合在一起时，医生和研究人员可以同时研究大脑的结构和活动。

When MRI and EEG are combined, it allows doctors and researchers to study both the structure and activity of the brain simultaneously.

MRI with EEG in Matplotlib

使用 Matplotlib，您可以创建可将 MRI 图像与 EEG 数据集成的可视化效果，让您能够探索和分析大脑功能和连接。

Matplotlib allows you to create visualizations that integrate MRI images with EEG data, enabling the exploration and analysis of brain function and connectivity.

在 Matplotlib 中，没有用于创建 MRI 与 EEG 可视化效果的特定功能。相反，您需要使用 Matplotlib 的绘图功能的组合，将 EEG 数据叠加到 MRI 图像上。这涉及单独加载和处理 MRI 和 EEG 数据，然后使用 Matplotlib 将它们显示在单个绘图中。

In Matplotlib, there isn’t a specific function for creating MRI with EEG visualizations. Instead, you need to use a combination of Matplotlib’s plotting functions to overlay EEG data onto MRI images. This involves loading and processing the MRI and EEG data separately, then using Matplotlib to display them together in a single plot.

您可以使用诸如 imshow() 之类的函数来显示 MRI 图像并使用 plot() 或 scatter() 将 EEG 数据叠加到 MRI 图像上。此外，您可以使用 Matplotlib 提供的各种自定义选项来调整绘图的外观和布局。

You can use functions like imshow() to display the MRI image and plot() or scatter() to overlay the EEG data onto the MRI image. Additionally, you can adjust the appearance and layout of the plot using various customization options provided by Matplotlib.

Displaying MRI Slice

在 Matplotlib 中，显示 MRI 切片包括可视化三维 MRI 体积的单个二维横截面。这可让您检查 MRI 扫描仪捕获的身体内部结构。您可以使用 Matplotlib 的绘图函数（例如 imshow()）将 MRI 切片加载并显示为绘图中的图像。

In Matplotlib, displaying an MRI slice involves visualizing a single two-dimensional cross-section of a three-dimensional MRI volume. This allows you to examine the internal structures of the body captured by the MRI scanner. You can load and display the MRI slice as an image within a plot using Matplotlib’s plotting functions, such as imshow().

Example

在以下示例中，我们使用 np.random.rand 生成合成 MRI 数据，创建一个表示 MRI 体素强度的随机数字 3D 数组。使用 Nibabel 的 nib.save 将此合成 MRI 数据保存到名为 'sample_mri.nii.gz' 的 NIfTI 文件。然后使用 nib.load 从已保存的文件加载合成 MRI 数据，并使用 Matplotlib 的 imshow() 函数显示 MRI 数据的单个切片（切片索引为 50）−

In the following example, we are generating synthetic MRI data using np.random.rand, creating a 3D array of random numbers representing MRI voxel intensities. We save this synthetic MRI data to a NIfTI file named 'sample_mri.nii.gz' using Nibabel’s nib.save. We then load the synthetic MRI data from the saved file using nib.load and display a single slice (slice index 50) of the MRI data using Matplotlib’s imshow() function−

import matplotlib.pyplot as plt
import nibabel as nib
import numpy as np

# Generating sample MRI data
sample_data = np.random.rand(100, 100, 100)

# Saving sample MRI data to a NIfTI file
nib.save(nib.Nifti1Image(sample_data, np.eye(4)), 'sample_mri.nii.gz')

# Loading sample MRI data
mri_img = nib.load('sample_mri.nii.gz')
mri_data = mri_img.get_fdata()

# Displaying a single MRI slice
plt.imshow(mri_data[:, :, 50], cmap='gray')
plt.title('Sample MRI Slice')
plt.axis('off')
plt.show()

以下是上面代码的输出： -

Following is the output of the above code −

mri with eeg1

Plot EEG Signal

在 Matplotlib 中绘制 EEG 信号包括可视化从放置在头皮上的电极记录的电活动。EEG 信号随着时间的推移表示大脑的神经活动，捕获与各种大脑状态和活动相关联的电位变化。

Plotting an EEG signal in Matplotlib involves visualizing the electrical activity recorded from electrodes placed on the scalp. EEG signals represent the brain’s neural activity over time, capturing changes in electrical potentials associated with various brain states and activities.

在 Matplotlib 中，您可以使用諸如 plot() 之类的函数绘制 EEG 数据，以显示信号随时间变化的幅度。EEG 绘图通常在 x 轴上有时间，在 y 轴上有电压或信号幅度，这让研究人员和临床医生可以分析大脑活动模式、检测异常并研究认知过程。

In Matplotlib, you can plot EEG data using functions like plot() to display the signal amplitude over time. EEG plots typically have time on the x-axis and voltage or signal amplitude on the y-axis, allowing researchers and clinicians to analyze brain activity patterns, detect abnormalities, and study cognitive processes.

Example

在这里，我们正在生成合成 EEG 数据，并使用 Matplotlib 的 plot() 函数绘制 EEG 信号随时间变化的情况 −

In here, we are generating synthetic EEG data and plotting the EEG signal over time using Matplotlib’s plot() function −

import matplotlib.pyplot as plt
import numpy as np

# Generating sample EEG data
# Sampling frequency (Hz)
fs = 1000
# Time vector (10 seconds)
t = np.arange(0, 10, 1/fs)
# Sample EEG signal
eeg_signal = np.sin(2 * np.pi * 10 * t) + 0.5 * np.random.randn(len(t))

# Plotting EEG signal
plt.plot(t, eeg_signal)
plt.title('EEG Signal')
plt.xlabel('Time (s)')
plt.ylabel('Amplitude')
plt.show()

执行上述代码，我们将得到以下输出 −

On executing the above code we will get the following output −

mri with eeg2

MRI Overlay with EEG Electrodes

在 Matplotlib 中，将 EEG 电极叠加到 MRI 图像上涉及将两种不同类型的医学数据结合用于可视化。MRI 可提供关于大脑结构的详细解剖信息，而 EEG 电极则可从大脑表面捕捉电信号。通过将 EEG 电极叠加到 MRI 图像上，研究人员和临床医生可以将大脑活动与特定大脑区域联系起来。

Overlaying EEG electrodes onto an MRI image in Matplotlib involves combining two different types of medical data for visualization. The MRI provides detailed anatomical information about the brain’s structures, while the EEG electrodes capture electrical signals from the brain’s surface. By overlaying EEG electrodes onto the MRI image, researchers and clinicians can correlate brain activity with specific brain regions.

你可以在 Matplotlib 中通过使用 imshow() 函数绘图 MRI 图像，然后使用符号或标记对 EEG 电极位置进行叠加，来实现此叠加。

You can achieve this overlay in Matplotlib by plotting the MRI image using the imshow() function and then superimposing the EEG electrode positions using symbols or markers.

Example

以下示例生成一个 MRI 图像，并使用 Matplotlib 在单个 MRI 切片上叠加 EEG 电极位置：

The following example generates an MRI image and overlays EEG electrode positions on a single MRI slice using Matplotlib −

import matplotlib.pyplot as plt
import numpy as np

# Generating synthetic MRI data
mri_shape = (100, 100, 100)
mri_data = np.random.rand(*mri_shape)

# Generating sample EEG electrode positions (x, y coordinates)
eeg_electrodes = np.array([[30, 40], [50, 60], [70, 80]])

# Displaying a single MRI slice
plt.imshow(mri_data[:, :, 50], cmap='gray')

# Overlaying EEG electrode positions
plt.scatter(eeg_electrodes[:, 0], eeg_electrodes[:, 1], color='red', marker='o', label='EEG Electrodes')

# Adding legend
plt.legend()

# Adding title and axis labels
plt.title('MRI Slice with EEG Electrodes')
plt.xlabel('X')
plt.ylabel('Y')

# Displaying plot
plt.show()

执行上面的代码后，我们得到以下输出： -

After executing the above code, we get the following output −

mri with eeg3