Exemplo n.º 1
0
def test_gk_dvh():
    # Given
    slicer_dvh_file = r'C:\Users\Victor\Dropbox\Plan_Competition_Project\tests\tests_data\gk_plan\SLICER_RT_DVH.csv'
    plan_folder = r'C:\Users\Victor\Dropbox\Plan_Competition_Project\tests\tests_data\gk_plan'

    slicer_dvh = read_slicer_dvh(slicer_dvh_file)

    # strip columns names
    slicer_dvh.columns = [
        'Skull Value', 'CerebelarDir', 'FrontalEsq ', 'Tumor', 'Tumor 2',
        'Tumor 3', 'Tumor 4', 'Tumor 5'
    ]

    dcm_files, flag = get_participant_folder_data(plan_folder)
    plan_dict = PyDicomParser(filename=dcm_files['rtplan']).GetPlan()
    structures = PyDicomParser(filename=dcm_files['rtss']).GetStructures()
    rd_dcm = PyDicomParser(filename=dcm_files['rtdose'])
    dose = rd_dcm.get_dose_3d()
    structures_py = [
        PyStructure(s, end_cap=s['thickness'] / 2)
        for k, s in structures.items()
    ]

    grid = (0.1, 0.1, 0.1)
    dvh_pyplan = {}
    for s in structures_py[:-1]:
        dvh_calci = DVHCalculation(s, dose, calc_grid=grid)
        dvh_l = dvh_calci.calculate(verbose=True)
        dvh_pyplan[dvh_l['name']] = dvh_l
        # plot_dvh(dvh_l, dvh_l['name'])

    for target_name, dvh_calc in dvh_pyplan.items():
        dose_t5 = slicer_dvh.index
        t5 = slicer_dvh.loc[:, target_name].values
        x_calc = np.arange(len(dvh_calc['data'])) * float(dvh_calc['scaling'])
        py_t5 = dvh_calc['data']

        plt.plot(dose_t5, t5, label='Slicer-RT')
        plt.plot(x_calc, py_t5, label='PyPlanScoring')
        plt.title(target_name)
        plt.legend()
        plt.show()
Exemplo n.º 2
0
    # filter rtdose
    rd_files = [d[1] for d in dicom_data if d[0] == 'rtdose']

    dcm_objs = [PyDicomParser(filename=rd_file) for rd_file in rd_files]
    doses_3d = [obj.get_dose_3d() for obj in dcm_objs]

    # Sum DVHs
    acc = DoseAccumulation(doses_3d)
    plan_sum = acc.get_plan_sum()

    # TODO compare with slicerRT plan sum DVH
    rs_file = '/home/victor/Dropbox/Plan_Competition_Project/tests/tests_data/left_chest_wall/photon_electron/RS.1.2.246.352.71.4.584747638204.283643.20180405155645.dcm'

    structures = PyDicomParser(filename=rs_file).GetStructures()
    structures_py = [
        PyStructure(s, end_cap=s['thickness']) for k, s in structures.items()
    ]

    dvh_pyplan = {}
    for s in structures_py:
        if s.name in eclipse_dvh.keys():
            if s.volume < 100:
                dvh_calci = DVHCalculation(s,
                                           plan_sum,
                                           calc_grid=(0.5, 0.5, 0.5))
            else:
                dvh_calci = DVHCalculation(s, plan_sum, calc_grid=None)
            dvh_l = dvh_calci.calculate(verbose=True)
            dvh_pyplan[dvh_l['name']] = dvh_l
            plot_dvh(dvh_l, dvh_l['name'])
            plt.plot(eclipse_dvh[s.name][:, 0],
Exemplo n.º 3
0
rs = os.path.join(DATA_DIR, 'RS.dcm')
rd = os.path.join(DATA_DIR, 'RD.dcm')
rp = os.path.join(DATA_DIR, 'RP.dcm')

str_names = [
    'LENS LT', 'PAROTID LT', 'BRACHIAL PLEXUS', 'OPTIC N. RT PRV',
    'OPTIC CHIASM PRV', 'OPTIC N. RT', 'ORAL CAVITY', 'BRAINSTEM',
    'SPINAL CORD', 'OPTIC CHIASM', 'LENS RT', 'LARYNX', 'SPINAL CORD PRV',
    'EYE LT', 'PTV56', 'BRAINSTEM PRV', 'PTV70', 'OPTIC N. LT PRV', 'EYE RT',
    'PTV63', 'OPTIC N. LT', 'LIPS', 'ESOPHAGUS', 'PTV70'
]

rs_dvh = os.path.join(DATA_DIR, 'RS_dvh.dcm')
structures_tmp = PyDicomParser(filename=rs_dvh).GetStructures()
to_index = {v['name']: k for k, v in structures_tmp.items()}


# fixtures
@pytest.fixture(scope="session")
def rp_dcm():
    """
        Fixture to return DICOM-RTPLAN obj
    :return:
    """
    return PyDicomParser(filename=rp)


@pytest.fixture(scope="session")
def rs_dcm():
    """