{"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":"code","source":"import numpy as np\nimport pandas as pd \nimport matplotlib.pyplot as plt \nimport cv2 as cv\nfrom path import Path\nimport os \nimport glob\nimport tensorflow_hub as hub\nimport os \nimport pydicom\nfrom pydicom.pixel_data_handlers.util import apply_voi_lut\nimport tensorflow as tf\nfrom tensorflow import keras\nfrom keras import layers\nfrom tqdm import tqdm\nfrom tensorflow.keras.preprocessing.image import load_img, img_to_array\nfrom tensorflow.keras.utils import to_categorical","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2022-03-31T20:09:10.765198Z","iopub.execute_input":"2022-03-31T20:09:10.765544Z","iopub.status.idle":"2022-03-31T20:09:16.330323Z","shell.execute_reply.started":"2022-03-31T20:09:10.765461Z","shell.execute_reply":"2022-03-31T20:09:16.329624Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_df= pd.read_csv('../input/rsna-miccai-brain-tumor-radiogenomic-classification/train_labels.csv')\nsample_df = pd.read_csv('../input/rsna-miccai-brain-tumor-radiogenomic-classification/sample_submission.csv')","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:09:16.33189Z","iopub.execute_input":"2022-03-31T20:09:16.332191Z","iopub.status.idle":"2022-03-31T20:09:16.355042Z","shell.execute_reply.started":"2022-03-31T20:09:16.332113Z","shell.execute_reply":"2022-03-31T20:09:16.354395Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def load_dicom(path):\n    dicom=pydicom.read_file(path)\n    data=dicom.pixel_array\n    data=data-np.min(data)\n    if np.max(data) != 0:\n        data=data/np.max(data)\n    data=(data*255).astype(np.uint8)\n    return data","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:09:16.358261Z","iopub.execute_input":"2022-03-31T20:09:16.358461Z","iopub.status.idle":"2022-03-31T20:09:16.364898Z","shell.execute_reply.started":"2022-03-31T20:09:16.358437Z","shell.execute_reply":"2022-03-31T20:09:16.364258Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def listdirs(folder):\n    return [d for d in os.listdir(folder) if os.path.isdir(os.path.join(folder, d))]","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:09:16.366148Z","iopub.execute_input":"2022-03-31T20:09:16.368472Z","iopub.status.idle":"2022-03-31T20:09:16.37346Z","shell.execute_reply.started":"2022-03-31T20:09:16.368435Z","shell.execute_reply":"2022-03-31T20:09:16.372507Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_dir='../input/rsna-miccai-brain-tumor-radiogenomic-classification/train'\ntrainset=[]\ntrainlabel=[]\ntrainidt=[]\nfor i in tqdm(range(len(train_df))):\n    idt=train_df.loc[i,'BraTS21ID']\n    idt2=('00000'+str(idt))[-5:]\n    path=os.path.join(train_dir,idt2,'T1wCE')              \n    for im in os.listdir(path):\n        img=load_dicom(os.path.join(path,im)) \n        img=cv.resize(img,(64,64)) \n        image=img_to_array(img)\n        image=image/255.0\n        trainset+=[image]\n        trainlabel+=[train_df.loc[i,'MGMT_value']]\n        trainidt+=[idt]","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:09:16.376292Z","iopub.execute_input":"2022-03-31T20:09:16.376603Z","iopub.status.idle":"2022-03-31T20:23:10.455327Z","shell.execute_reply.started":"2022-03-31T20:09:16.376567Z","shell.execute_reply":"2022-03-31T20:23:10.454646Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_dir='../input/rsna-miccai-brain-tumor-radiogenomic-classification/test'\ntestset=[]\ntestidt=[]\nfor i in tqdm(range(len(sample_df))):\n    idt=sample_df.loc[i,'BraTS21ID']\n    idt2=('00000'+str(idt))[-5:]\n    path=os.path.join(test_dir,idt2,'T1wCE')               \n    for im in os.listdir(path):   \n        img=load_dicom(os.path.join(path,im))\n        img=cv.resize(img,(64,64)) \n        image=img_to_array(img)\n        image=image/255.0\n        testset+=[image]\n        testidt+=[idt]","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:23:10.456871Z","iopub.execute_input":"2022-03-31T20:23:10.45736Z","iopub.status.idle":"2022-03-31T20:25:22.343135Z","shell.execute_reply.started":"2022-03-31T20:23:10.45731Z","shell.execute_reply":"2022-03-31T20:25:22.342448Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"y=np.array(trainlabel)\nY_train=to_categorical(y)\nX_train=np.array(trainset)\nX_test=np.array(testset)","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:25:22.344617Z","iopub.execute_input":"2022-03-31T20:25:22.34509Z","iopub.status.idle":"2022-03-31T20:25:24.777931Z","shell.execute_reply.started":"2022-03-31T20:25:22.34505Z","shell.execute_reply":"2022-03-31T20:25:24.777003Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"model = keras.models.Sequential()\nmodel.add(keras.layers.Conv2D(filters=64,kernel_size=(4,4),input_shape=(64,64,1),activation='relu',kernel_initializer=\"he_normal\"))\nmodel.add(keras.layers.MaxPooling2D(pool_size=(2,2)))\nmodel.add(keras.layers.BatchNormalization())\nmodel.add(keras.layers.Conv2D(filters=64,kernel_size=(4,4),activation='relu',kernel_initializer=\"he_normal\"))\nmodel.add(keras.layers.MaxPooling2D(pool_size=(2,2)))\nmodel.add(keras.layers.Dropout(0.20))\nmodel.add(keras.layers.BatchNormalization())\nmodel.add(keras.layers.Conv2D(filters=64,kernel_size=(4,4),activation='relu',kernel_initializer=\"he_normal\"))\nmodel.add(keras.layers.MaxPooling2D(pool_size=(2,2)))\nmodel.add(keras.layers.Dropout(0.25))\nmodel.add(keras.layers.BatchNormalization())\nmodel.add(keras.layers.Flatten())\nmodel.add(keras.layers.Dense(100,activation=\"relu\",kernel_initializer=\"he_normal\"))\nmodel.add(keras.layers.Dense(2,\"softmax\"))","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:25:24.779285Z","iopub.execute_input":"2022-03-31T20:25:24.779552Z","iopub.status.idle":"2022-03-31T20:25:27.473325Z","shell.execute_reply.started":"2022-03-31T20:25:24.779517Z","shell.execute_reply":"2022-03-31T20:25:27.471537Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"model.summary()","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:25:27.474574Z","iopub.execute_input":"2022-03-31T20:25:27.474812Z","iopub.status.idle":"2022-03-31T20:25:27.488078Z","shell.execute_reply.started":"2022-03-31T20:25:27.474777Z","shell.execute_reply":"2022-03-31T20:25:27.487402Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"model.compile(loss=\"categorical_crossentropy\",\n              optimizer = \"RMSprop\",metrics=[\"accuracy\"])","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:25:27.490955Z","iopub.execute_input":"2022-03-31T20:25:27.491137Z","iopub.status.idle":"2022-03-31T20:25:27.504378Z","shell.execute_reply.started":"2022-03-31T20:25:27.491114Z","shell.execute_reply":"2022-03-31T20:25:27.503756Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"callback = keras.callbacks.EarlyStopping(monitor='loss', patience=8)","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:25:27.507077Z","iopub.execute_input":"2022-03-31T20:25:27.507259Z","iopub.status.idle":"2022-03-31T20:25:27.513244Z","shell.execute_reply.started":"2022-03-31T20:25:27.507236Z","shell.execute_reply":"2022-03-31T20:25:27.512502Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"hist = model.fit(X_train, Y_train,epochs=100, batch_size=64, verbose=1,callbacks=[callback])","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:25:27.514519Z","iopub.execute_input":"2022-03-31T20:25:27.514876Z","iopub.status.idle":"2022-03-31T20:47:52.724241Z","shell.execute_reply.started":"2022-03-31T20:25:27.51484Z","shell.execute_reply":"2022-03-31T20:47:52.72337Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"get_ac = hist.history['accuracy']\nget_los = hist.history['loss']\n","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:47:52.725858Z","iopub.execute_input":"2022-03-31T20:47:52.726247Z","iopub.status.idle":"2022-03-31T20:47:52.988488Z","shell.execute_reply.started":"2022-03-31T20:47:52.726205Z","shell.execute_reply":"2022-03-31T20:47:52.987771Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"epochs = range(len(get_ac))\nplt.plot(epochs, get_ac, 'g', label='Accuracy of Training data')\nplt.plot(epochs, get_los, 'r', label='Loss of Training data')\nplt.title('Training data accuracy and loss')\nplt.legend(loc=0)\nplt.figure()\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:47:53.174109Z","iopub.execute_input":"2022-03-31T20:47:53.174383Z","iopub.status.idle":"2022-03-31T20:47:53.362095Z","shell.execute_reply.started":"2022-03-31T20:47:53.174337Z","shell.execute_reply":"2022-03-31T20:47:53.361383Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"y_pred=model.predict(X_test)\npred=np.argmax(y_pred,axis=1)\nresult=pd.DataFrame(testidt)\nresult[1]=pred\nresult.columns=['BraTS21ID','MGMT_value']\nresult2=result.groupby('BraTS21ID',as_index=False).mean()\nresult2","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:47:53.548145Z","iopub.execute_input":"2022-03-31T20:47:53.548427Z","iopub.status.idle":"2022-03-31T20:47:54.861886Z","shell.execute_reply.started":"2022-03-31T20:47:53.548366Z","shell.execute_reply":"2022-03-31T20:47:54.861203Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"result2['BraTS21ID']=sample_df['BraTS21ID']\nresult2['MGMT_value']=result2['MGMT_value'].apply(lambda x:round(x*10)/10)\nresult2.to_csv('submission.csv',index=False)\nresult2","metadata":{"execution":{"iopub.status.busy":"2022-03-31T20:48:58.025311Z","iopub.execute_input":"2022-03-31T20:48:58.025644Z","iopub.status.idle":"2022-03-31T20:48:58.045042Z","shell.execute_reply.started":"2022-03-31T20:48:58.025614Z","shell.execute_reply":"2022-03-31T20:48:58.044317Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}