{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 5GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"filename","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"# authors : Guillaume Lemaitre <g.lemaitre58@gmail.com>\n# license : MIT\n\nimport matplotlib.pyplot as plt\nimport pydicom\nfrom pydicom.data import get_testdata_files\n\nprint(__doc__)\n\nfile_path = '/kaggle/input/rsna-str-pulmonary-embolism-detection/test/00268ff88746/75d23269adbd/012c12fe09c3.dcm'\ndataset = pydicom.dcmread(file_path)\n\n\nif 'PixelData' in dataset:\n    rows = int(dataset.Rows)\n    cols = int(dataset.Columns)\n    print(\"Image size.......: {rows:d} x {cols:d}, {size:d} bytes\".format(\n        rows=rows, cols=cols, size=len(dataset.PixelData)))\n    if 'PixelSpacing' in dataset:\n        print(\"Pixel spacing....:\", dataset.PixelSpacing)\n\n# use .get() if not sure the item exists, and want a default value if missing\nprint(\"Slice location...:\", dataset.get('SliceLocation', \"(missing)\"))\n\n# plot the image using matplotlib\nplt.imshow(dataset.pixel_array, cmap=plt.cm.bone)\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"dataset","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4}