python医学影像3Dnii文件转成2Ddicom文件(保留原始dicom信息)

1.原始的每个DCE序列中有多个dicom文件,经过插值裁剪后转成以一个3Dmatnii矩阵
2.现在的需求是把处理过的3Dnii矩阵还原成2Ddicom文件,并且保留原始dicom信息.

1.插值裁剪后的影像数据

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每一个.nii.gz文件代表DCE-MRI中的一个序列

2.原始DCE-MRI影像数据中一个序列包含多个dcm文件

image.png

3.Python代码:把3Dnii文件还原成2Ddicom文件,并且保留原始dicom信息.

导入需要的包

import os
import SimpleITK as sitk
import numpy as np
import pydicom as dicom

定义翻转函数实现图像的180°旋转

def flip180(arr):#图片反转180°
    new_arr =arr.copy()
    new_arr = arr.reshape(arr.size)
    new_arr = new_arr[::-1]
    new_arr = new_arr.reshape(arr.shape)
    return new_arr

定义给dicom的tag赋值的函数

def modify_dicom(ds,dcm):#把原始dicom的元数据写进新的dicom中，否则无法成为一个序列
     #PatientInfo
    ds.PatientID = dcm.PatientID
    ds.PatientName =  dcm.PatientName
    ds.PatientBirthDate = dcm.PatientBirthDate
    ds.PatientSex = dcm.PatientSex
    ds.PatientAge = dcm.PatientAge
    ds.PatientWeight = dcm.PatientWeight
    try:
        ds.MagneticFieldStrength = dcm.MagneticFieldStrength
        ds.Manufacturer = dcm.Manufacturer
    except TypeError:
        print("Error:没有InstitutionName、Manufacturer、InstitutionName tag")
    #studyInfo
    ds.StudyDate =dcm.StudyDate
    ds.StudyTime = dcm.StudyTime
    ds.StudyDescription = dcm.StudyDescription
    ds.StudyInstanceUID = dcm.StudyInstanceUID
    ds.StudyID = ds.StudyID
    # seriesInfo
    ds.SeriesInstanceUID = dcm.SeriesInstanceUID 
    ds.SeriesDescription = dcm.SeriesDescription
    ds.Modality = dcm.Modality
    ds.SeriesNumber = dcm.SeriesNumber
    #ds.InstanceNumber  = instanceNumber #Instance Number    
    ds.SeriesDate = dcm.SeriesDate
    ds.SeriesTime = dcm.SeriesTime
    ds.SOPClassUID = dcm.SOPClassUID
    return ds

定义给nii转dicom的核心函数

def nii2dicom(nii_img,save_dir,DCE_MR):
    
    """[将重采样后的nii图片转dicom保存]
    Args:
        nii_img ([]): 一个3维nii类型，shape=(W,H,切片数)
        save_dir ([type]): 转成dicom序列文件保存路径
    """
    itk_img = sitk.ReadImage(nii_img)    
    img_3Dndarray = sitk.GetArrayFromImage(itk_img)#得到图像矩阵
    img_shape = img_3Dndarray.shape
    print(img_shape,img_shape[0])#查看 3D 维度
    img_num = img_3Dndarray.shape[0]
    
    PixelSpacing = itk_img.GetMetaData('pixdim[1]')#pixdim[1] : 0.379464 pixdim[2] : 0.379464 pixel spacing
    SliceThickness =  itk_img.GetMetaData('pixdim[3]')#pixdim[3] : 1.2  层厚
    BitsAllocated =  itk_img.GetMetaData('bitpix')#16
    Columns = itk_img.GetMetaData('dim[1]')#dim[1] : 896
    Rows = itk_img.GetMetaData('dim[2]')
    for i in range(img_num-13):
        #从第13张slice开始，13张之前的均是不完整的切片
        ####.nii切片倒着读，并旋转180度,也要变为int16才行 img_num-i-1
        out = flip180(img_3Dndarray[12+i,:,:]).astype('uint16')
        itk_img_1 = sitk.GetImageFromArray(out)
        InstanceNumber = ''
        if (i+1) <10:
            InstanceNumber = '0000'+str(i+1)
        elif (i+1) <100:
            InstanceNumber = '000'+str(i+1)
        elif (i+1) <300:
            InstanceNumber = '00'+str(i+1)
        else:
            print('Warning!!',InstanceNumber,"dicom数量大于300")
        dicom_save_file_path = save_dir+'\\'+InstanceNumber+'.dcm'#to do i range
        itk_img_1.SetMetaData('0028|0030',PixelSpacing)#0028,0030 修改 Pixel Spacing: 1.5625信息
        itk_img_1.SetMetaData('0018|0050',SliceThickness)
        itk_img_1.SetMetaData('0028|0100',str(16))#bitpix : 16  位数
        itk_img_1.SetMetaData('0028|0011',Columns)#Columns
        itk_img_1.SetMetaData('0028|0010',Rows)#Rows
        itk_img_1.SetMetaData('0020|0013',str(i+1))#instanceNumber
        sitk.WriteImage(itk_img_1,dicom_save_file_path)

        ######再读文件，修改dicom的tag信息使这些图片成为一个序列
        read_dicom_path = DCE_MR+'\\'+'00010.dcm'  #原始dcm文件的具体路径
        dcm = dicom.read_file(read_dicom_path)
        ds = dicom.read_file(dicom_save_file_path)
        if i == 0:
            seriesInstanceUID = ds.SeriesInstanceUID
            studyInstanceUID = ds.StudyInstanceUID
            frameUID = ds[0X0020, 0X0052].value 
        else:
            ds.SeriesInstanceUID = seriesInstanceUID #修改Series Instance UID
            ds.StudyInstanceUID = studyInstanceUID
            ds[0X0020, 0X0052].value = frameUID
        ds = modify_dicom(ds,dcm)
        ds.InstanceNumber = i+1 ###必须加，形成连续变化的序列，不然，dicom软件读取切片会变乱
        ds.save_as(dicom_save_file_path)

返回具体nii文件的路径

def get_NII_path(root_path,niidata_path,reliceniidata_path):
    '''
    返回具体nii文件的路径
    '''
    count_study = 0
    for every_study in os.listdir(niidata_path):#遍历所有的病历号
        count_study +=1
        tmp_MR_path = os.path.join(root_path,every_study,'MR')#DWI ,T2等
        _renii_path =os.path.join(reliceniidata_path,every_study)
        if count_study <80:
            continue
        for every_MRI in os.listdir(tmp_MR_path):#每个病历号下面可能有多次MRI
            tmp_MRI_path = os.path.join(tmp_MR_path,every_MRI)
            tmp_DCEseries = tmp_MRI_path+"\DCE00000"
            DCE_length = len(os.listdir(tmp_DCEseries))
            print(tmp_DCEseries,"-->",DCE_length)
            _rdicom_path = os.path.join(niidata_path,every_study,'ResliceMR',every_MRI)
            for every_nii in os.listdir(_renii_path):
                if DCE_length!=112 and "corDCE0000" in every_nii:
                    str1 = every_nii.replace(".nii.gz","")
                    str2 = str1.replace("cor","")
                    DCE_MR = os.path.join(tmp_MRI_path,str2)
                    every_niidata = os.path.join(_renii_path,every_nii)
                    print(every_niidata)
                    save_rDCE = os.path.join(_rdicom_path,str1)
                    if not os.path.exists(save_rDCE):
                        os.makedirs(save_rDCE)
                        print("create-->"+save_rDCE+"-->successfully!!")
                    else:
                        print(save_rDCE+" have exists!")
                    nii2dicom(every_niidata,save_rDCE,DCE_MR)

定义路径,调用函数执行

if __name__ =="__main__":
    root_path = r"G:\DCE+T2+ADC"
    niidata_path = r"G:\DCE90_NiiDATA"
    reliceniidata_path =r"G:\DCE_ResliceNiiDATA"
    get_NII_path(root_path,niidata_path,reliceniidata_path)

代码执行过程：

image.png

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