This Util library designed for some common used functions in bee lab: +Yoshioka
- Download
- pip install -r requirements.txt
- add this foldar path to you PYTHONPATH
For MRI users, you can use this util to read dicom data generated from 7T Bruker MRI,
Example: after we export dicom datas from Bruker MRI, we can save them to the folder called "raw_data",
+ raw_data
++++++ liu-20200212_liu-20200212_stell__E15_P1_2.16.756.5.5.100.3611282843.14246.1581486821.87
+++++++++++ MRIm1
+++++++++++ MRIm2
+++++++++++ MRIm3
The below codes can read and show the images (in jupyter notebook).
from Util.os import readMRIfromIds
from Util.plot.staticPlot import *
rootDir = './raw_data/'
Images = readMRIfromIds(rootDir,[15])
plotMRIImage(Images[:,:,0],updown=False,axis=False)
# for multiple datas:
Img1 = readMRIfromIds('./data/',[13,14,15,16,17])
# will return:
#Dicom Files readed to array with shape : (256, 256, 5)
#Dicom Files readed to array with shape : (256, 256, 5)
#Dicom Files readed to array with shape : (256, 256, 5)
#Dicom Files readed to array with shape : (256, 256, 5)
#Dicom Files readed to array with shape : (256, 256, 5)
# shape of Img1 will be (256,256,25)For TMS spfd users,you can visulize the coil and brain segementation file by:
from Util.os.spfd import *
convSPFD = spfd()
convSPFD.visCoil("output_coil_vis","coil.csv","coil_position.txt")
# ouput vtk name will be output_coil_vis.vtu
dx,dy,dz = 1,1,1
convSPFD.visBrain("brain_map.csv",(dx,dy,dz))
# ouput vtk name will be brain_map_visBrain.vtithan you can confirm the coil position with brain in Paraview
After the simulation you can convert result.txt file to vector file like this:
convSPFD.visJ(output_j_vtk_path,result_file_path)