使用pydicom從軸向視圖中提取矢狀和冠狀切口

Question

我正在嘗試閱讀一系列.dcm文件，這些文件默認情況下顯示軸向視圖。 下面是代碼：

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)

從代碼中可以看到，我無法弄清楚特定dcm文件的相關idx和idy。 所以我的問題是，在軸向切開的情況下，如何獲得矢狀切面和冠狀切面並繪制它們？

提前致謝。

編輯：作為@ColonelFazackerley完美回答。 我在下面添加一行只是為了說明如何使用它。

# 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()

根據本示例3D CT數據針對系列2進行了測試， 網址為http://www.pcir.org/researchers/54879843_20060101.html

編輯說明：接受作為pydicom項目的示例https://github.com/pydicom/pydicom/blob/master/examples/image_processing/reslice.py