Create pydicom file from numpy array

Question

I'm trying to create a mew dicom image from a standard-sized (512 x 512 or 256 x 256) numpy array. It seems like this should be straightforward, and I've adapted my code from http://code.google.com/p/pydicom/source/browse/source/dicom/examples/write_new.py, which appears to execute the same process, but when I save the file, I can't view it either in RadiAnt or MicroDicom.

import dicom, dicom.UID
from dicom.dataset import Dataset, FileDataset

def write_dicom(pixel_array,filename):

    file_meta = Dataset()
    ds = FileDataset(filename, {},file_meta = file_meta,preamble="\0"*128)
    ds.PixelData = pixel_array.tostring()
    ds.save_as(filename)
    return

if __name__ == "__main__":
    import numpy as np
    pixel_array = np.tile(np.arange(256).reshape(16,16), (16,16)) * 4
    write_dicom(pixel_array,'pretty.dcm')

Answer 1

Here is a functional version of the code I needed to write. It will write a 16-bit grayscale DICOM image from a given 2D array of pixels. According to the DICOM standard, the UIDs should be unique for each image and series, which this code doesn't worry about, because I don't know what the UIDs actually do. If anyone else does, I'll be happy to add it in.

import dicom, dicom.UID
from dicom.dataset import Dataset, FileDataset
import numpy as np
import datetime, time

def write_dicom(pixel_array,filename):
    """
    INPUTS:
    pixel_array: 2D numpy ndarray.  If pixel_array is larger than 2D, errors.
    filename: string name for the output file.
    """

    ## This code block was taken from the output of a MATLAB secondary
    ## capture.  I do not know what the long dotted UIDs mean, but
    ## this code works.
    file_meta = Dataset()
    file_meta.MediaStorageSOPClassUID = 'Secondary Capture Image Storage'
    file_meta.MediaStorageSOPInstanceUID = '1.3.6.1.4.1.9590.100.1.1.111165684411017669021768385720736873780'
    file_meta.ImplementationClassUID = '1.3.6.1.4.1.9590.100.1.0.100.4.0'
    ds = FileDataset(filename, {},file_meta = file_meta,preamble="\0"*128)
    ds.Modality = 'WSD'
    ds.ContentDate = str(datetime.date.today()).replace('-','')
    ds.ContentTime = str(time.time()) #milliseconds since the epoch
    ds.StudyInstanceUID =  '1.3.6.1.4.1.9590.100.1.1.124313977412360175234271287472804872093'
    ds.SeriesInstanceUID = '1.3.6.1.4.1.9590.100.1.1.369231118011061003403421859172643143649'
    ds.SOPInstanceUID =    '1.3.6.1.4.1.9590.100.1.1.111165684411017669021768385720736873780'
    ds.SOPClassUID = 'Secondary Capture Image Storage'
    ds.SecondaryCaptureDeviceManufctur = 'Python 2.7.3'

    ## These are the necessary imaging components of the FileDataset object.
    ds.SamplesPerPixel = 1
    ds.PhotometricInterpretation = "MONOCHROME2"
    ds.PixelRepresentation = 0
    ds.HighBit = 15
    ds.BitsStored = 16
    ds.BitsAllocated = 16
    ds.SmallestImagePixelValue = '\\x00\\x00'
    ds.LargestImagePixelValue = '\\xff\\xff'
    ds.Columns = pixel_array.shape[0]
    ds.Rows = pixel_array.shape[1]
    if pixel_array.dtype != np.uint16:
        pixel_array = pixel_array.astype(np.uint16)
    ds.PixelData = pixel_array.tostring()

    ds.save_as(filename)
    return



if __name__ == "__main__":
#    pixel_array = np.arange(256*256).reshape(256,256)
#    pixel_array = np.tile(np.arange(256).reshape(16,16),(16,16))
    x = np.arange(16).reshape(16,1)
    pixel_array = (x + x.T) * 32
    pixel_array = np.tile(pixel_array,(16,16))
    write_dicom(pixel_array,'pretty.dcm')