Python 3D图像分割在分水岭距离图中寻找局部峰值

import numpy as np
import scipy.ndimage as ndimage
import scipy.ndimage.filters as filters
import matplotlib.pyplot as plt

# 读取3D图像数据
image = np.load('image.npy')

# 计算梯度幅值图
gradient = filters.sobel(image)

# 计算分水岭距离图
distance = ndimage.distance_transform_edt(gradient)

# 使用最大值滤波器寻找局部峰值
local_maxima = filters.maximum_filter(distance, size=3) == distance

# 使用掩码过滤非局部峰值
background = (distance == 0)
local_maxima &= ~background

# 获取局部峰值的坐标
coordinates = np.transpose(np.nonzero(local_maxima))

# 可视化分水岭距离图和局部峰值
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 5))
ax1.imshow(distance, cmap='gray')
ax1.set_title('Distance Map')
ax2.imshow(image, cmap='gray')
ax2.scatter(coordinates[:, 1], coordinates[:, 0], c='r', s=5)
ax2.set_title('Local Maxima')
plt.show()