{"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_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"Entire credit of this notebook goes to below notebook, kindly upvote and appreciate the original work there\n\n* https://www.kaggle.com/davidbroberts/determining-mr-image-planes","metadata":{}},{"cell_type":"code","source":"import os\nimport numpy as np\nimport pandas as pd\nimport pydicom\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.axes_grid1 import ImageGrid","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#samp = pd.read_csv('../input/rsna-miccai-brain-tumor-radiogenomic-classification/sample_submission.csv')","metadata":{"execution":{"iopub.status.busy":"2021-07-14T13:45:17.030675Z","iopub.execute_input":"2021-07-14T13:45:17.031014Z","iopub.status.idle":"2021-07-14T13:45:17.047189Z","shell.execute_reply.started":"2021-07-14T13:45:17.030984Z","shell.execute_reply":"2021-07-14T13:45:17.04624Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import random \nmain_dir = '../input/rsna-miccai-brain-tumor-radiogenomic-classification/test'\n\nsub_dirs = [dI for dI in os.listdir(main_dir) if os.path.isdir(os.path.join(main_dir,dI))]\n\nsub = pd.DataFrame(columns = ['BraTS21ID','MGMT_value'])\n\nnums = [0,1]\n\nfor s in sub_dirs:\n    \n    \n    sub.loc[len(sub.index)] = [s, random.choice(nums)]\n\nsub.MGMT_value = sub.MGMT_value.astype(float)\nsub.BraTS21ID = sub.BraTS21ID.astype(float) #int->float","metadata":{"execution":{"iopub.status.busy":"2021-07-14T14:40:32.411478Z","iopub.execute_input":"2021-07-14T14:40:32.411871Z","iopub.status.idle":"2021-07-14T14:40:32.690993Z","shell.execute_reply.started":"2021-07-14T14:40:32.411834Z","shell.execute_reply":"2021-07-14T14:40:32.690057Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sub.to_csv(\"submission.csv\",index=False)","metadata":{"execution":{"iopub.status.busy":"2021-07-14T13:45:17.337528Z","iopub.execute_input":"2021-07-14T13:45:17.337901Z","iopub.status.idle":"2021-07-14T13:45:17.344308Z","shell.execute_reply.started":"2021-07-14T13:45:17.337862Z","shell.execute_reply":"2021-07-14T13:45:17.343262Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#directory = '../input/rsna-miccai-brain-tumor-radiogenomic-classification'\n\n#def get_series_list(dataset, study_id, series):\n#    series_list = []\n\n    #for subdirs, dirs, files in os.walk(directory + '/' + dataset + '/' + study_id + \"/\" + series):\n#    series_list = os.listdir(directory + '/' + dataset + '/' + study_id + '/' + series)\n            \n#    return series_list","metadata":{"execution":{"iopub.status.busy":"2021-07-14T13:45:17.346017Z","iopub.execute_input":"2021-07-14T13:45:17.346495Z","iopub.status.idle":"2021-07-14T13:45:17.358411Z","shell.execute_reply.started":"2021-07-14T13:45:17.346421Z","shell.execute_reply":"2021-07-14T13:45:17.357316Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\n#study_id = '00005'\n#series = 'T2w'\n#dataset = 'train'\n\n#series_files = get_series_list(dataset,study_id, series)\n\n#series_df = pd.DataFrame(columns = ['image','instance_number'])\n\n#for s in series_files:\n\n#    img = pydicom.dcmread(directory + \"/\" + dataset + \"/\" + study_id + \"/\" + series + \"/\" + s)\n#    if img.pixel_array.mean() > 0:\n#        series_df.loc[len(series_df.index)] = [s, img[0x0020,0x0013].value]\n\n#series_df['instance_number'] = pd.to_numeric(series_df['instance_number'])\n\n#series_df = series_df.sort_values(by=['instance_number'])\n\n#fig = plt.figure(figsize=(16, 16))\n#grid = ImageGrid(fig, 111, nrows_ncols=(10, 10), axes_pad=0.1)\n#count = 0\n\n#series_list = series_df.image.tolist()\n    \n#for ax, img in zip(grid, series_list):\n#    count += 1\n\n#    image = pydicom.dcmread(directory + \"/\" + dataset + \"/\" + study_id + \"/\" + series + \"/\" + img)\n\n#    ax.imshow(image.pixel_array, cmap='gray')\n#    if count > 100:\n#        break","metadata":{"execution":{"iopub.status.busy":"2021-07-14T13:45:17.360234Z","iopub.execute_input":"2021-07-14T13:45:17.360771Z","iopub.status.idle":"2021-07-14T13:45:17.371801Z","shell.execute_reply.started":"2021-07-14T13:45:17.360662Z","shell.execute_reply":"2021-07-14T13:45:17.370827Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#img_file = '../input/rsna-miccai-brain-tumor-radiogenomic-classification/train/00005/T2w/Image-201.dcm'\n#img = pydicom.dcmread(img_file)\n\n#pixels = img.pixel_array\n\n#plt.figure(figsize=(8,8))\n#plt.imshow(pixels,cmap='gray');","metadata":{"execution":{"iopub.status.busy":"2021-07-14T13:45:17.373442Z","iopub.execute_input":"2021-07-14T13:45:17.373945Z","iopub.status.idle":"2021-07-14T13:45:17.390116Z","shell.execute_reply.started":"2021-07-14T13:45:17.373904Z","shell.execute_reply":"2021-07-14T13:45:17.388947Z"},"trusted":true},"execution_count":null,"outputs":[]}]}