Question

我正在尝试读取一系列.dcm文件，这些文件默认情况下显示轴向视图。下面是代码：

import os
import numpy as np
import pydicom as dicom
from matplotlib import pyplot as plt

root_dir = 'mydcomDir'


def sortDcm():
        print('Given Path to the .dcm directory is: {}'.format(root_dir))
        slices = [dicom.read_file(root_dir + '/' + s) for s in os.listdir(root_dir)]
        slices.sort(key = lambda x: float(x.ImagePositionPatient[2]))
        pos1 = slices[int(len(slices)/2)].ImagePositionPatient[2]
        pos2 = slices[(int(len(slices)/2)) + 1].ImagePositionPatient[2]
        diff = pos2 - pos1
#        if diff > 0:
#            slices = np.flipud(slices)
        try:
            slice_thickness = np.abs(slices[0].ImagePositionPatient[2] - slices[1].ImagePositionPatient[2])
        except:
            slice_thickness = np.abs(slices[0].SliceLocation - slices[1].SliceLocation)

        for s in slices:
            s.SliceThickness = slice_thickness
#        print("from sorted dicom",len(slices))         
        return slices 


dcms = sortDcm()
ref_dicom = dcms[0]

d_array = np.zeros((ref_dicom.Columns,ref_dicom.Rows, len(dcms)), dtype=ref_dicom.pixel_array.dtype)

for dcm in dcms:
    d_array[:, :, dcms.index(dcm)] = dcm.pixel_array

#    fig = plt.figure(figsize=(12,12))
#    plt.subplot(1, 3, 1)
#    plt.title("Coronal")
#    plt.imshow(np.flipud(d_array[idx , :, :].T))
#    plt.subplot(1, 3, 2)
#    plt.title("Sagital")
#    plt.imshow(np.flipud(d_array[:, idy, :].T))
#    plt.subplot(1, 3, 3)
    plt.title("axial")
    plt.imshow(d_array[:, :, dcms.index(dcm)])
    plt.pause(0.001)

从代码中可以看到，我无法确定特定dcm文件的相关idx和idy。所以我的问题是，在轴向切开的情况下，如何获得矢状切面和冠状切面并绘制它们？

先谢谢了。

编辑：正如@ColonelFazackerley完美回答。我在下面添加一行只是为了显示我如何使用它。

# fill 3D array with the images from the files
for i, s in enumerate(slices):
    img2d = s.pixel_array
    img3d[:,:,i] = img2d
#then to view sagittal and coronal slices for each of the axial slice
for i, s in enumerate(slices):
    img2d = s.pixel_array
    img3d[:,:,i] = img2d
    corId = corId-1
    sagId = sagId-1
#    plot 3 orthogonal slices
    a1 = plt.subplot(1,3,1)
    plt.title('Axial')
    plt.imshow(img3d[:,:,i],'gray')
    a1.set_aspect(ax_aspect)

    a2 = plt.subplot(1,3,2)
    plt.title('Sagittal')
    plt.imshow(np.flipud(img3d[:,sagId,:].T),'gray')
    a2.set_aspect(sag_aspect)

    a3 = plt.subplot(1,3,3)
    plt.imshow(np.flipud(img3d[corId,:,:].T),'gray')
    a3.set_aspect(cor_aspect)
    plt.title('Coronal')
    plt.show()
    plt.pause(0.001)

Answer 1

"""usage: reslice.py <glob>
where <glob> refers to a set of DICOM image files.

Example: python reslice.py "*.dcm". The quotes are needed to protect the glob
from your system and leave it for the script."""

import pydicom
import numpy as np
import matplotlib.pyplot as plt
import sys
import glob

# load the DICOM files
files=[]
print('glob: {}'.format(sys.argv[1]))
for fname in glob.glob(sys.argv[1], recursive=False):
    print("loading: {}".format(fname))
    files.append(pydicom.read_file(fname))

print("file count: {}".format(len(files)))

# skip files with no SliceLocation (eg scout views)
slices=[]
skipcount=0
for f in files:
    if hasattr(f, 'SliceLocation'):
        slices.append(f)
    else:
        skipcount = skipcount + 1

print("skipped, no SliceLocation: {}".format(skipcount))

# ensure they are in the correct order
slices = sorted(slices, key=lambda s: s.SliceLocation)

# pixel aspects, assuming all slices are the same
ps = slices[0].PixelSpacing
ss = slices[0].SliceThickness
ax_aspect = ps[1]/ps[0]
sag_aspect = ps[1]/ss
cor_aspect = ss/ps[0]

# create 3D array
img_shape = list(slices[0].pixel_array.shape)
img_shape.append(len(slices))
img3d=np.zeros(img_shape)

# fill 3D array with the images from the files
for i, s in enumerate(slices):
    img2d = s.pixel_array
    img3d[:,:,i] = img2d

# plot 3 orthogonal slices
a1 = plt.subplot(2,2,1)
plt.imshow(img3d[:,:,img_shape[2]//2])
a1.set_aspect(ax_aspect)

a2 = plt.subplot(2,2,2)
plt.imshow(img3d[:,img_shape[1]//2,:])
a2.set_aspect(sag_aspect)

a3 = plt.subplot(2,2,3)
plt.imshow(img3d[img_shape[0]//2,:,:].T)
a3.set_aspect(cor_aspect)

plt.show()

根据此示例3D CT数据针对系列2进行了测试 http://www.pcir.org/researchers/54879843_20060101.html

编辑说明：作为pydicom项目的示例被接受 https://github.com/pydicom/pydicom/blob/master/examples/image_processing/reslice.py

使用pydicom从轴向视图中提取矢状和冠状切口

1 个答案: