Python Image.argmax方法代码示例

# 需要导入模块: from msct_image import Image [as 别名]
# 或者: from msct_image.Image import argmax [as 别名]
def get_centerline_from_point(input_image, point_file, gap=4, gaussian_kernel=4, remove_tmp_files=1):

    # Initialization
    fname_anat = input_image
    fname_point = point_file
    slice_gap = gap
    remove_tmp_files = remove_tmp_files
    gaussian_kernel = gaussian_kernel
    start_time = time()
    verbose = 1

    # get path of the toolbox
    status, path_sct = commands.getstatusoutput("echo $SCT_DIR")
    path_sct = sct.slash_at_the_end(path_sct, 1)

    # Parameters for debug mode
    if param.debug == 1:
        sct.printv("\n*** WARNING: DEBUG MODE ON ***\n\t\t\tCurrent working directory: " + os.getcwd(), "warning")
        status, path_sct_testing_data = commands.getstatusoutput("echo $SCT_TESTING_DATA_DIR")
        fname_anat = path_sct_testing_data + "/t2/t2.nii.gz"
        fname_point = path_sct_testing_data + "/t2/t2_centerline_init.nii.gz"
        slice_gap = 5

    # check existence of input files
    sct.check_file_exist(fname_anat)
    sct.check_file_exist(fname_point)

    # extract path/file/extension
    path_anat, file_anat, ext_anat = sct.extract_fname(fname_anat)
    path_point, file_point, ext_point = sct.extract_fname(fname_point)

    # extract path of schedule file
    # TODO: include schedule file in sct
    # TODO: check existence of schedule file
    file_schedule = path_sct + param.schedule_file

    # Get input image orientation
    input_image_orientation = get_orientation_3d(fname_anat, filename=True)

    # Display arguments
    print "\nCheck input arguments..."
    print "  Anatomical image:     " + fname_anat
    print "  Orientation:          " + input_image_orientation
    print "  Point in spinal cord: " + fname_point
    print "  Slice gap:            " + str(slice_gap)
    print "  Gaussian kernel:      " + str(gaussian_kernel)
    print "  Degree of polynomial: " + str(param.deg_poly)

    # create temporary folder
    print ("\nCreate temporary folder...")
    path_tmp = "tmp." + strftime("%y%m%d%H%M%S")
    sct.create_folder(path_tmp)
    print "\nCopy input data..."
    sct.run("cp " + fname_anat + " " + path_tmp + "/tmp.anat" + ext_anat)
    sct.run("cp " + fname_point + " " + path_tmp + "/tmp.point" + ext_point)

    # go to temporary folder
    os.chdir(path_tmp)

    # convert to nii
    im_anat = convert("tmp.anat" + ext_anat, "tmp.anat.nii")
    im_point = convert("tmp.point" + ext_point, "tmp.point.nii")

    # Reorient input anatomical volume into RL PA IS orientation
    print "\nReorient input volume to RL PA IS orientation..."
    set_orientation(im_anat, "RPI")
    im_anat.setFileName("tmp.anat_orient.nii")
    # Reorient binary point into RL PA IS orientation
    print "\nReorient binary point into RL PA IS orientation..."
    # sct.run(sct.fsloutput + 'fslswapdim tmp.point RL PA IS tmp.point_orient')
    set_orientation(im_point, "RPI")
    im_point.setFileName("tmp.point_orient.nii")

    # Get image dimensions
    print "\nGet image dimensions..."
    nx, ny, nz, nt, px, py, pz, pt = Image("tmp.anat_orient.nii").dim
    print ".. matrix size: " + str(nx) + " x " + str(ny) + " x " + str(nz)
    print ".. voxel size:  " + str(px) + "mm x " + str(py) + "mm x " + str(pz) + "mm"

    # Split input volume
    print "\nSplit input volume..."
    im_anat_split_list = split_data(im_anat, 2)
    file_anat_split = []
    for im in im_anat_split_list:
        file_anat_split.append(im.absolutepath)
        im.save()

    im_point_split_list = split_data(im_point, 2)
    file_point_split = []
    for im in im_point_split_list:
        file_point_split.append(im.absolutepath)
        im.save()

    # Extract coordinates of input point
    data_point = Image("tmp.point_orient.nii").data
    x_init, y_init, z_init = unravel_index(data_point.argmax(), data_point.shape)
    sct.printv("Coordinates of input point: (" + str(x_init) + ", " + str(y_init) + ", " + str(z_init) + ")", verbose)

    # Create 2D gaussian mask
    sct.printv("\nCreate gaussian mask from point...", verbose)
#.........这里部分代码省略.........

# 需要导入模块: from msct_image import Image [as 别名]
# 或者: from msct_image.Image import argmax [as 别名]

#.........这里部分代码省略.........
    # go to temporary folder
    os.chdir(path_tmp)

    # convert to nii
    convert('tmp.anat'+ext_anat, 'tmp.anat.nii')
    convert('tmp.point'+ext_point, 'tmp.point.nii')

    # Reorient input anatomical volume into RL PA IS orientation
    print '\nReorient input volume to RL PA IS orientation...'
    #sct.run(sct.fsloutput + 'fslswapdim tmp.anat RL PA IS tmp.anat_orient')
    set_orientation('tmp.anat.nii', 'RPI', 'tmp.anat_orient.nii')
    # Reorient binary point into RL PA IS orientation
    print '\nReorient binary point into RL PA IS orientation...'
    # sct.run(sct.fsloutput + 'fslswapdim tmp.point RL PA IS tmp.point_orient')
    set_orientation('tmp.point.nii', 'RPI', 'tmp.point_orient.nii')

    # Get image dimensions
    print '\nGet image dimensions...'
    nx, ny, nz, nt, px, py, pz, pt = Image('tmp.anat_orient.nii').dim
    print '.. matrix size: '+str(nx)+' x '+str(ny)+' x '+str(nz)
    print '.. voxel size:  '+str(px)+'mm x '+str(py)+'mm x '+str(pz)+'mm'

    # Split input volume
    print '\nSplit input volume...'
    split_data('tmp.anat_orient.nii', 2, '_z')
    file_anat_split = ['tmp.anat_orient_z'+str(z).zfill(4) for z in range(0, nz, 1)]
    split_data('tmp.point_orient.nii', 2, '_z')
    file_point_split = ['tmp.point_orient_z'+str(z).zfill(4) for z in range(0, nz, 1)]

    # Extract coordinates of input point
    # sct.printv('\nExtract the slice corresponding to z='+str(z_init)+'...', verbose)
    #
    data_point = Image('tmp.point_orient.nii').data
    x_init, y_init, z_init = unravel_index(data_point.argmax(), data_point.shape)
    sct.printv('Coordinates of input point: ('+str(x_init)+', '+str(y_init)+', '+str(z_init)+')', verbose)

    # Create 2D gaussian mask
    sct.printv('\nCreate gaussian mask from point...', verbose)
    xx, yy = mgrid[:nx, :ny]
    mask2d = zeros((nx, ny))
    radius = round(float(gaussian_kernel+1)/2)  # add 1 because the radius includes the center.
    sigma = float(radius)
    mask2d = exp(-(((xx-x_init)**2)/(2*(sigma**2)) + ((yy-y_init)**2)/(2*(sigma**2))))

    # Save mask to 2d file
    file_mask_split = ['tmp.mask_orient_z'+str(z).zfill(4) for z in range(0,nz,1)]
    nii_mask2d = Image('tmp.anat_orient_z0000.nii')
    nii_mask2d.data = mask2d
    nii_mask2d.setFileName(file_mask_split[z_init]+'.nii')
    nii_mask2d.save()
    #
    # # Get the coordinates of the input point
    # print '\nGet the coordinates of the input point...'
    # data_point = Image('tmp.point_orient.nii').data
    # x_init, y_init, z_init = unravel_index(data_point.argmax(), data_point.shape)
    # print '('+str(x_init)+', '+str(y_init)+', '+str(z_init)+')'

    # x_init, y_init, z_init = (data > 0).nonzero()
    # x_init = x_init[0]
    # y_init = y_init[0]
    # z_init = z_init[0]
    # print '('+str(x_init)+', '+str(y_init)+', '+str(z_init)+')'
    #
    # numpy.unravel_index(a.argmax(), a.shape)
    #
    # file = nibabel.load('tmp.point_orient.nii')