sql_db_get.py

from sqlalchemy import create_engine
from sqlalchemy.ext.automap import automap_base
from sqlalchemy.orm import sessionmaker
from tag import Image_Para,Patient_Info
import SimpleITK as sitk
import os
import pydicom
import numpy
from matplotlib import pyplot
from PIL import Image
import PIL
from vtkmodules.util import numpy_support
import cv2
import io
import shortuuid


# 1. 准备连接数据库基本信息
# 计算机ip地址
HOSTNAME = '127.0.0.1'
# 端口号
PORT = '3306'
# 连接数据库的名字
DATABASE = 'image_data'
# 数据库的账号和密码
USERNAME = 'root'
PASSWORD = 'zhy210320'
# 创建数据库引擎
DB_URI = 'mysql+mysqlconnector://{username}:{pwd}@{host}:{port}/{db}?charset=utf8'\
    .format(username =USERNAME,pwd = PASSWORD,host = HOSTNAME,port=PORT,db = DATABASE)
engine = create_engine(DB_URI,encoding='utf-8',echo=False)

# 基于ORM的反射
Base = automap_base()
Base.prepare(engine, reflect=True)
tables = Base.classes
#  print(Base.classes.keys())   # 数据库包含的列表

# 获取对应表格映射
baseinfo = Base.classes.baseinfo
patient = Base.classes.patient
image_para = Base.classes.image_para

# 获取实例
Session = sessionmaker(bind=engine)
session = Session()

# 添加信息
# PathDicom = 'E:/Dicom/test/DicomResource'
# para = Image_Para(PathDicom)
# session.add(image_para(id='1',study_id=para['StudyID'],study_date=para['StudyDate'],study_time=para['StudyTime'],dimsize=str(para['DimSize']),origin=str(para['Orign']),spacing=str(para['Spacing']),window_width=str(para['WindowWidth']),window_center=str(para['WindowCenter']),institution_name=para['InstitutionName'],manufacturer=para['Manufacturer'],image_address=para['Address']))
# # session.add(patient(id='1',patient_id=patient_info['ID'],patient_age=patient_info['Age'],patient_bd=patient_info['BirthDate'],patient_sex=patient_info['Sex'],patient_size=patient_info['Size'],patient_weight=patient_info['Weight']))
# session.commit()




PathDicom = "E:/Dicom/test/DicomResource"  # 与python文件同一个目录下的文件夹
lstFilesDCM = []
DcmName = []
for dirName, subdirList, fileList in sorted(os.walk(PathDicom)):
    for filename in fileList:
        if ".dcm" in filename.lower():  # 判断文件是否为dicom文件
            # print(filename)
            lstFilesDCM.append(os.path.join(dirName, filename))  # 加入到列表中
            DcmName.append(filename)
# print(dirName)
# print(subdirList)
# print(fileList)

RefDs = pydicom.read_file(lstFilesDCM[0])

reader = sitk.ImageSeriesReader()
dicom_names = reader.GetGDCMSeriesFileNames(PathDicom)
reader.SetFileNames(dicom_names)
image = reader.Execute()
columns = RefDs.Columns
row = RefDs.Rows
ConstOrigin = image.GetOrigin()
ConstPixelSpacing = image.GetSpacing()
ConstPixelDims = (int(row), int(columns), len(lstFilesDCM))
image_1 = int(ConstPixelDims[0] // 2)
image_2 = int(ConstPixelDims[1] // 2)
image_3 = int(ConstPixelDims[2] // 2)
x = numpy.arange(0.0, (ConstPixelDims[0] + 1) * ConstPixelSpacing[0],
                 ConstPixelSpacing[0])  # 0到（第一个维数加一*像素间的间隔），步长为constpixelSpacing
y = numpy.arange(0.0, (ConstPixelDims[1] + 1) * ConstPixelSpacing[1], ConstPixelSpacing[1])  #
z = numpy.arange(0.0, (ConstPixelDims[2] + 1) * ConstPixelSpacing[2], ConstPixelSpacing[2])  #
ArrayDicom = numpy.zeros(ConstPixelDims, dtype=RefDs.pixel_array.dtype)

# 遍历所有的dicom文件，读取图像数据，存放在numpy数组中
for filenameDCM in lstFilesDCM:
    ds = pydicom.read_file(filenameDCM)
    ArrayDicom[:, :, lstFilesDCM.index(filenameDCM)] = ds.pixel_array
'''
fig1 = pyplot.figure(dpi=300)
pyplot.axes().set_aspect('equal','datalim')
pyplot.set_cmap(pyplot.gray())
pyplot.pcolormesh(x, y, numpy.flipud(ArrayDicom[:, :, image_3]))  # 第三个维度表示现在展示的是第几层
pyplot.axis('off')
buffer_ = io.BytesIO()
pyplot.savefig(buffer_,format='png')
buffer_.seek(0)
img1 = PIL.Image.open(buffer_)
img_arr1 = numpy.asarray(img1)
buffer_.close()

fig2 = pyplot.figure(dpi=300)
pyplot.axes().set_aspect('equal','datalim')
pyplot.set_cmap(pyplot.gray())
pyplot.pcolormesh(y, z, numpy.fliplr(numpy.rot90((ArrayDicom[image_1, :, :]),3)))
pyplot.axis('off')
buffer_ = io.BytesIO()
pyplot.savefig(buffer_,format='png')
buffer_.seek(0)
img2 = PIL.Image.open(buffer_)
img_arr2 = numpy.asarray(img2)
buffer_.close()

fig3 = pyplot.figure(dpi=300)
pyplot.axes().set_aspect('equal','datalim')
pyplot.set_cmap(pyplot.gray())
pyplot.pcolormesh(x, z, numpy.fliplr(numpy.rot90((ArrayDicom[:, image_2, :]),3)))
pyplot.axis('off')
buffer_ = io.BytesIO()
pyplot.savefig(buffer_,format='png')
buffer_.seek(0)
img3 = PIL.Image.open(buffer_)
img_arr3 = numpy.asarray(img3)
buffer_.close()

pyplot.figure(figsize=(3,1),dpi=300)
pyplot.subplot(131)
pyplot.imshow(img_arr1)
pyplot.title('AxialSlice',fontsize=4,y=0.9)
pyplot.axis('off')
pyplot.xticks([])
pyplot.yticks([])
pyplot.subplot(132)
pyplot.imshow(img_arr2)
pyplot.title('CoronalSlice',fontsize=4,y=0.9)
pyplot.axis('off')
pyplot.xticks([])
pyplot.yticks([])
pyplot.subplot(133)
pyplot.imshow(img_arr3)
pyplot.title('SagitalSlice',fontsize=4,y=0.9)
pyplot.axis('off')
pyplot.xticks([])
pyplot.yticks([])
pyplot.tight_layout(pad=0.5,w_pad=2)
pyplot.subplots_adjust(wspace=0,hspace=0)
# pyplot.savefig('E:\\Dicom\\test\\images\\'+'image.jpg')
pyplot.savefig('E:\\Dicom\\test\\images\\'+'image.jpg')
pyplot.show()
'''
'''
pyplot.figure(dpi=300)
pyplot.axes().set_aspect('equal')
pyplot.set_cmap(pyplot.gray())
pyplot.pcolormesh(x, y, numpy.flipud(ArrayDicom[:, :, image_3]))  # 第三个维度表示现在展示的是第几层
pyplot.axis('off')
pyplot.savefig('E:\\Dicom\\test\\images\\'+'AxialSlice'+'.jpg',bbox_inches='tight',pad_inches=0.0)
pyplot.show()




pyplot.figure(dpi=300)
pyplot.axes().set_aspect('equal')
pyplot.set_cmap(pyplot.gray())
pyplot.pcolormesh(y, z, numpy.fliplr(numpy.rot90((ArrayDicom[image_1, :, :]),3)))
pyplot.axis('off')
pyplot.savefig('E:\\Dicom\\test\\images\\'+'CoronalSlice'+'.jpg',bbox_inches='tight',pad_inches=0.0)
pyplot.show()

pyplot.figure(dpi=300)
pyplot.axes().set_aspect('equal')
pyplot.set_cmap(pyplot.gray())
pyplot.pcolormesh(x, z, numpy.fliplr(numpy.rot90((ArrayDicom[:, image_2, :]),3)))
pyplot.axis('off')
pyplot.savefig('E:\\Dicom\\test\\images\\'+'SagitalSlice'+'.jpg',bbox_inches='tight',pad_inches=0.0)
pyplot.show()

'''
'''
Array_vtk = numpy_support.numpy_to_vtk(ArrayDicom.ravel('F'), deep=True, array_type=vtk.VTK_FLOAT)
imagedata = vtk.vtkImageData()
imagedata.SetOrigin(ConstOrigin)
imagedata.SetSpacing(ConstPixelSpacing)
imagedata.SetDimensions(ConstPixelDims)
imagedata.GetPointData().SetScalars(Array_vtk)
origin = numpy.array(ConstOrigin)
ConstPixelSpacing = numpy.array(ConstPixelSpacing)
ConstPixelDims = numpy.array(ConstPixelDims)
center = origin + (ConstPixelSpacing * ConstPixelDims / 2)
DirectionCosines_x = (0, 0, 1, 0, 1, 0, -1, 0, 0)
DirectionCosines_y = (1, 0, 0, 0, 0, -1, 0, 1, 0)
DirectionCosines_z = (1, 0, 0, 0, 1, 0, 0, 0, 1)

def mip_x():
    ImageSlab = vtk.vtkImageSlabReslice()
    ImageSlab.SetInputData(imagedata)
    ImageSlab.SetResliceAxesOrigin(center)
    ImageSlab.SetResliceAxesDirectionCosines(DirectionCosines_x)
    ImageSlab.SetSlabThickness(ConstPixelSpacing[0]*ConstPixelDims[0])
    ImageSlab.SetBlendModeToMax()
    ImageSlab.SetSlabResolution(ConstPixelSpacing[0])
    ImageSlab.Update()
    image = ImageSlab.GetOutput()
    m = image.GetDimensions()
    vtk_data = image.GetPointData().GetScalars()
    arr = numpy_support.vtk_to_numpy(vtk_data).reshape(m[1], m[0])
    arr = (arr - numpy.min(arr)) / ((numpy.max(arr) - numpy.min(arr)) / 255)
    width = RefDs.Columns
    height = int(len(lstFilesDCM) * (ConstPixelSpacing[2] / ConstPixelSpacing[1]))
    dim = (width, height)
    resized = cv2.resize(numpy.rot90(arr, 1), dim, interpolation=cv2.INTER_AREA)
    return resized

def mip_y():
    ImageSlab = vtk.vtkImageSlabReslice()
    ImageSlab.SetInputData(imagedata)
    ImageSlab.SetResliceAxesOrigin(center)
    ImageSlab.SetResliceAxesDirectionCosines(DirectionCosines_y)
    ImageSlab.SetSlabThickness(ConstPixelSpacing[1]*ConstPixelDims[1])
    ImageSlab.SetBlendModeToMax()
    ImageSlab.SetSlabResolution(ConstPixelSpacing[1])
    ImageSlab.Update()
    image = ImageSlab.GetOutput()
    m = image.GetDimensions()
    vtk_data = image.GetPointData().GetScalars()
    arr = numpy_support.vtk_to_numpy(vtk_data).reshape(m[1], m[0])
    arr = (arr - numpy.min(arr)) / ((numpy.max(arr) - numpy.min(arr)) / 255)
    width = int(len(lstFilesDCM) * (ConstPixelSpacing[2] / ConstPixelSpacing[0]))
    height = RefDs.Rows
    dim = (width, height)
    resized = cv2.resize(numpy.rot90(arr, -1), dim, interpolation=cv2.INTER_AREA)
    # cv2.imwrite( path +'/'+ name +'.jpg', resized)
    return resized

def mip_z():
    ImageSlab = vtk.vtkImageSlabReslice()
    ImageSlab.SetInputData(imagedata)
    ImageSlab.SetResliceAxesOrigin(center)
    ImageSlab.SetResliceAxesDirectionCosines(DirectionCosines_z)
    ImageSlab.SetSlabThickness(ConstPixelSpacing[2] * ConstPixelDims[2])
    ImageSlab.SetBlendModeToMax()
    ImageSlab.SetSlabResolution(ConstPixelSpacing[2])
    ImageSlab.Update()
    image = ImageSlab.GetOutput()
    m = image.GetDimensions()
    vtk_data = image.GetPointData().GetScalars()
    arr = numpy_support.vtk_to_numpy(vtk_data).reshape(m[1], m[0])
    arr = (arr - numpy.min(arr)) / ((numpy.max(arr) - numpy.min(arr)) / 255)
    arr = numpy.rot90(arr,-1)
    # cv2.imwrite(path+'/'+name+'.jpg', numpy.rot90(arr, -1))
    return arr


pyplot.figure(figsize=(3,1),dpi=300)
pyplot.subplot(131)
pyplot.imshow(mip_z(),cmap='gray')
pyplot.title('AxialSlice_MIP',fontsize=4,y=1.1)
pyplot.xticks([])
pyplot.yticks([])
pyplot.subplot(132)
pyplot.imshow(mip_x(),cmap='gray')
pyplot.title('CoronalSlice_MIP',fontsize=4,y=1.1)
pyplot.xticks([])
pyplot.yticks([])
pyplot.subplot(133)
pyplot.imshow(numpy.rot90(mip_y(),1),cmap='gray')
pyplot.title('SagitalSlice_MIP',fontsize=4,y=1.1)
pyplot.xticks([])
pyplot.yticks([])
pyplot.tight_layout(pad=1.3,w_pad=2)
pyplot.subplots_adjust(wspace=0,hspace=0)
pyplot.savefig('E:\\Dicom\\test\\images\\'+'MIP_image.jpg')
pyplot.show()
'''

i = 0
for i in range(len(lstFilesDCM)):
    info = {}
    info['id'] = shortuuid.uuid()
    info['filename'] = DcmName[i]
    info['modality'] = RefDs.Modality
    info['bodypart'] = RefDs.BodyPartExamined
    info['address'] = dirName + '/' + DcmName[i]
    info['type'] = 'dcm'
    session.add(baseinfo(id=info['id'],file_name=info['filename'],modality=info['modality'],body_part=info['bodypart'],file_address=info['address'],data_type=info['type'],patient_id=info['p_id'],image_id=info['i_id']))
    session.commit()
    i = i+1