可以在 Python 中将 3D numpy 数组转换为 3D 图像吗？

Question

我在 3D 阵列中制作了以下虚拟“房间”，并希望将其可视化。 我找不到方法，请帮忙。 我们的想法是将阵列的“3D 图像”视为不同值具有不同颜色或只是灰度强度的图，以便您可以看到“房间”内的“患者”和“检测器”：

import numpy as np


# Diff. values in the Room define objects: 0 = walls, 1 = inside room, 2 = patient's tissue, 3 = bone, 4 = x-ray detector

Room = np.array([[[0.0 for i in range(0,101,1)] for j in range(0,101,1)] for k in range(0,101,1)]) #The entire room with walls

for i in range(1,100,1):
    for j in range(1,100,1):
        for k in range(1,100,1):
            Room[i,j,k] +=1     # The room not counting the walls

for i in range(30,70,1):
    for j in range(30,70,1):
        for k in range(30,70,1):
            Room[i,j,k] +=1      #The patient's body (tissue)
            
for i in range(50,55,1):
    for j in range(50,55,1):
        for k in range(50,55,1):
            Room[i,j,k] +=1      #The patient's bone #1 
            
for i in range(58,63,1):
    for j in range(58,63,1):
        for k in range(58,63,1):
            Room[i,j,k] +=1      #The patient's bone #2

for i in range(88,92,1):
    for j in range(10,90,1):
        for k in range(10,90,1):
            Room[i,j,k] +=1      # X-ray Detector

Answer 1

您可以在 matplotlib 和 numpy 的帮助下创建 3 维网格。 这是一个这样的情节的例子。 您只想将 X、Y 和 Z 值作为列表输入

import numpy as np
import matplotlib.pyplot as plt

# Create figure and add axis
fig = plt.figure(figsize=(8,6))
ax = plt.subplot(111, projection='3d')
    
# Remove gray panes and axis grid
ax.xaxis.pane.fill = False
ax.xaxis.pane.set_edgecolor('white')
ax.yaxis.pane.fill = False
ax.yaxis.pane.set_edgecolor('white')
ax.zaxis.pane.fill = False
ax.zaxis.pane.set_edgecolor('white')
ax.grid(False)
# Remove z-axis
ax.w_zaxis.line.set_lw(0.)
ax.set_zticks([])
    
# Create meshgrid
X, Y = np.meshgrid(np.linspace(0, 2, len(afm_data)), np.linspace(0, 2, len(afm_data)))
    
# Plot surface
plot = ax.plot_surface(X=X, Y=Y, Z=Z, cmap='YlGnBu_r', vmin=0, vmax=200)

Towards Data Science还有一篇关于此主题的文章： https ://towardsdatascience.com/visualizing-three-dimensional-data-heatmaps-contours-and-3d-plots-with-python-bd718d1b42b4

Answer 2

只是重新添加这个，因为第一个答案在我有机会回复之前就被删除了：

您在寻找体积渲染方法吗？ 有大量具有该功能的 Python 库可供使用。 这是一个示例链接。

对于您的具体情况，您可以使用例如 plotly，我刚刚根据他们的教程为您的数据编写了一个快速脚本：

import numpy as np
import plotly.graph_objects as go

# Generate nicely looking random 3D-field
np.random.seed(0)
l = 5
X, Y, Z = np.mgrid[:l, :l, :l]
vol = np.zeros((l, l, l))
#pts = (l * np.random.rand(3, 15)).astype(np.int)


# Diff. values in the Room define objects: 0 = walls, 1 = inside room, 2 = patient's tissue, 3 = bone, 4 = x-ray detector

Room = np.array([[[0.0 for i in range(0,102,1)] for j in range(0,102,1)] for k in range(0,102,1)]) #The entire room with walls

for i in range(1,100,1):
    for j in range(1,100,1):
        for k in range(1,100,1):
            Room[i,j,k] +=1     # The room not counting the walls

for i in range(30,70,1):
    for j in range(30,70,1):
        for k in range(30,70,1):
            Room[i,j,k] +=1      #The patient's body (tissue)
            
for i in range(50,55,1):
    for j in range(50,55,1):
        for k in range(50,55,1):
            Room[i,j,k] +=1      #The patient's bone #1 
            
for i in range(58,63,1):
    for j in range(58,63,1):
        for k in range(58,63,1):
            Room[i,j,k] +=1      #The patient's bone #2

for i in range(88,92,1):
    for j in range(10,90,1):
        for k in range(10,90,1):
            Room[i,j,k] +=1      # X-ray Detector

pts = Room.reshape(3,353736).astype(np.int)

print( tuple(indices for indices in pts) )

vol[tuple(indices for indices in pts)] = 1

from scipy import ndimage

vol = ndimage.gaussian_filter(vol, 0.5)
vol /= vol.max()

fig = go.Figure(data=go.Volume(
    x=X.flatten(), y=Y.flatten(), z=Z.flatten(),
    value=vol.flatten(),
    isomin=0.2,
    isomax=0.7,
    opacity=0.1,
    surface_count=25,
    ))
fig.update_layout(scene_xaxis_showticklabels=False,
                  scene_yaxis_showticklabels=False,
                  scene_zaxis_showticklabels=False)
fig.show()

输出如下。 不确定这是否是您的想法。