{"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":"# **RSNA-MICCAI Brain Tumor Radiogenomic Classification**😀\n脳腫瘍治療に重要な遺伝子バイオマーカーの状態を予測する\n\n※ English version is here.\nhttps://www.kaggle.com/chumajin/brain-tumor-eda-for-starter-english-version\n\n## このコンペは、MRIの画像から**脳腫瘍治療に重要な遺伝子バイオマーカーであるMGMTプロモーターのメチル化**を予測するコンペだと思います。\n\n\n私みたいに専門外の人には、ちょっと何言っているかわからないと思います。\n\nMGMTという遺伝子のプロモーター領域のメチル化の状態によって、化学療法に対する反応や予後が異なることが報告されているみたいです。\n\n最近では、このメチル化の検査を参考にすることで、手術後の治療として、放射線治療か、化学療法かを適切に選択することができ、\n\nこれが患者さんの状態をよく保ちながら生存期間を延ばすことに役立つことがわかってきたみたいです。\n※ https://www.h.u-tokyo.ac.jp/neurosurg/rinsho/noushu.htm を参考。\n\n\n初め脳腫瘍かどうかを当てるコンペだと思ったのですが、そうではなく(English版でコメントもらいました)、\n\nこのデータセットに含まれるすべての被験者は脳腫瘍（膠芽腫）を持っているみたいです。\n\nクラス0は、腫瘍がない人ではなく、MGMTプロモーターというもののメチル化がない人を指します。1はある人みたいです。それの確率を出すコンペです。\n\n\n## 少しでもお役に立てば、upvoteして頂けると嬉しいです。\n　※　以前も私のnotebookにupvoteしてくれた方ありがとうございます。\n  ※ ver3以前は勘違いをしていました。ご指摘ありがとうございました(English version)\n  \n  ※ ver13～ dcmファイルの中身を見て、SliceLocationから、Scanごとの位置合わせを実行 (2.6～)","metadata":{}},{"cell_type":"code","source":"import numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport os\n","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2021-08-04T14:44:32.635415Z","iopub.execute_input":"2021-08-04T14:44:32.635945Z","iopub.status.idle":"2021-08-04T14:44:32.648698Z","shell.execute_reply.started":"2021-08-04T14:44:32.635785Z","shell.execute_reply":"2021-08-04T14:44:32.647432Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 1. 何を予測するか(submission.csvから見ます)","metadata":{}},{"cell_type":"code","source":"sample = pd.read_csv(\"../input/rsna-miccai-brain-tumor-radiogenomic-classification/sample_submission.csv\")\nsample","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:44:32.653608Z","iopub.execute_input":"2021-08-04T14:44:32.653935Z","iopub.status.idle":"2021-08-04T14:44:32.796005Z","shell.execute_reply.started":"2021-08-04T14:44:32.653902Z","shell.execute_reply":"2021-08-04T14:44:32.794764Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## BraTS21IDは患者のId、\n\n\n* MGMT_valueはクラス0は、初め脳腫瘍がない人と思っていたのですが、MGMTプロモーターというもののメチル化がない人みたいです。\n\n* 1はある人（腫瘍内の遺伝子配列があると、化学療法に対する反応性の好ましい予後因子および強力な予測因子。)これを予測します。","metadata":{}},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 2. 何から予測するか ? train.csvを見ていく","metadata":{}},{"cell_type":"markdown","source":"## 2.1 train.csvとファイル構成","metadata":{}},{"cell_type":"markdown","source":"### test.csvはないので、train.csvを見てみます。","metadata":{}},{"cell_type":"code","source":"train = pd.read_csv(\"../input/rsna-miccai-brain-tumor-radiogenomic-classification/train_labels.csv\")\ntrain","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:45:01.10794Z","iopub.execute_input":"2021-08-04T14:45:01.108511Z","iopub.status.idle":"2021-08-04T14:45:01.129103Z","shell.execute_reply.started":"2021-08-04T14:45:01.108461Z","shell.execute_reply":"2021-08-04T14:45:01.127967Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"submissionとほぼ同じ情報。BraTS21IDは患者のId、MGMT_valueはMGMT promoterにメチル化があるかどうかの情報が載っています。\n\n\nこのtrainデータには、以下のように、\n\n\nそれぞれ、FLAIR,T1w,T1wCE,T2wがあって、その中にdcmファイルがぶら下がっています。","metadata":{}},{"cell_type":"markdown","source":"![image.png](attachment:f62278ec-cdeb-40d3-bf9c-3031fd13c359.png)\n\nそれぞれのIDに FLAIR, T1w, T1wCE, T2wというのが、紐づいています。","metadata":{},"attachments":{"f62278ec-cdeb-40d3-bf9c-3031fd13c359.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"![image.png](attachment:43a5e528-5750-4b79-876b-0eed0745bf27.png)\n\nそれぞれにたくさんのdcmファイルがある。","metadata":{},"attachments":{"43a5e528-5750-4b79-876b-0eed0745bf27.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"## 2.2 dcmファイルを1枚見てみる。","metadata":{}},{"cell_type":"markdown","source":"dcmファイルがどんなものか見るために、まず１枚dcmファイルを開く","metadata":{}},{"cell_type":"code","source":"import pydicom\nimport matplotlib.pyplot as plt\n\ndataset = pydicom.filereader.dcmread('../input/rsna-miccai-brain-tumor-radiogenomic-classification/train/00000/FLAIR/Image-109.dcm')\nimg = dataset.pixel_array\n\nfig, ax = plt.subplots()\nax.imshow(img, cmap='gray')\nax.set_axis_off()\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:45:03.293859Z","iopub.execute_input":"2021-08-04T14:45:03.294258Z","iopub.status.idle":"2021-08-04T14:45:03.710017Z","shell.execute_reply.started":"2021-08-04T14:45:03.29422Z","shell.execute_reply":"2021-08-04T14:45:03.708888Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"imgにするところだけ関数化します。（後程使います)","metadata":{}},{"cell_type":"code","source":"def makeimg(path):\n    dataset = pydicom.filereader.dcmread(path)\n    img = dataset.pixel_array\n    return img","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:45:04.375025Z","iopub.execute_input":"2021-08-04T14:45:04.375436Z","iopub.status.idle":"2021-08-04T14:45:04.380314Z","shell.execute_reply.started":"2021-08-04T14:45:04.375404Z","shell.execute_reply":"2021-08-04T14:45:04.378933Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 2.3 FLAIR, T1w, T1wCE, T2wのイメージの代表例を見ていく。","metadata":{}},{"cell_type":"markdown","source":"pathを出した後この関数を使って、FLAIR, T1w, T1wCE, T2wのイメージの代表例を見てみます.\n\n\nその前に、それぞれのフォルダーにdcmファイルが同じ数あるのか確認します。","metadata":{}},{"cell_type":"markdown","source":"### 2.3.1 dcmフォルダパスの作成","metadata":{}},{"cell_type":"markdown","source":"まず、dcm imageのパスを出していくことを考えます","metadata":{"execution":{"iopub.status.busy":"2021-07-14T14:46:23.097356Z","iopub.execute_input":"2021-07-14T14:46:23.097731Z","iopub.status.idle":"2021-07-14T14:46:23.105586Z","shell.execute_reply.started":"2021-07-14T14:46:23.097697Z","shell.execute_reply":"2021-07-14T14:46:23.103941Z"}}},{"cell_type":"code","source":"train[\"imfolder\"] = ['{0:05d}'.format(s) for s in train[\"BraTS21ID\"]]\ntrain","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:45:06.007807Z","iopub.execute_input":"2021-08-04T14:45:06.008336Z","iopub.status.idle":"2021-08-04T14:45:06.027365Z","shell.execute_reply.started":"2021-08-04T14:45:06.008283Z","shell.execute_reply":"2021-08-04T14:45:06.026319Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_path = \"../input/rsna-miccai-brain-tumor-radiogenomic-classification/train\"\n\ntrain[\"path\"] = [os.path.join(train_path,s) for s in train[\"imfolder\"]  ]\ntrain","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:45:06.311514Z","iopub.execute_input":"2021-08-04T14:45:06.312144Z","iopub.status.idle":"2021-08-04T14:45:06.330051Z","shell.execute_reply.started":"2021-08-04T14:45:06.312107Z","shell.execute_reply":"2021-08-04T14:45:06.329154Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Scansとして、リスト化するとあとあとfor文で回しやすいです。","metadata":{}},{"cell_type":"code","source":"Scans = [\"FLAIR\",\"T1w\",\"T1wCE\",\"T2w\"]","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:45:06.866702Z","iopub.execute_input":"2021-08-04T14:45:06.867224Z","iopub.status.idle":"2021-08-04T14:45:06.871929Z","shell.execute_reply.started":"2021-08-04T14:45:06.867189Z","shell.execute_reply":"2021-08-04T14:45:06.870564Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 2.3.2 dcmファイルの数の確認","metadata":{}},{"cell_type":"markdown","source":"そもそもこれらScansのdcmの数が、患者ごとに同じなのかを確認します。","metadata":{}},{"cell_type":"code","source":"from tqdm import tqdm","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:45:07.781234Z","iopub.execute_input":"2021-08-04T14:45:07.781621Z","iopub.status.idle":"2021-08-04T14:45:07.786541Z","shell.execute_reply.started":"2021-08-04T14:45:07.781585Z","shell.execute_reply":"2021-08-04T14:45:07.785408Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"1. まずはtrainの0行目のFLAIRのパスは以下のように表せます。","metadata":{}},{"cell_type":"code","source":"train.head(3)","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:45:08.331957Z","iopub.execute_input":"2021-08-04T14:45:08.332558Z","iopub.status.idle":"2021-08-04T14:45:08.343476Z","shell.execute_reply.started":"2021-08-04T14:45:08.332521Z","shell.execute_reply":"2021-08-04T14:45:08.342644Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"os.path.join(train[\"path\"].iloc[0],\"FLAIR\")","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:45:08.595855Z","iopub.execute_input":"2021-08-04T14:45:08.596417Z","iopub.status.idle":"2021-08-04T14:45:08.603943Z","shell.execute_reply.started":"2021-08-04T14:45:08.596382Z","shell.execute_reply":"2021-08-04T14:45:08.60282Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"2. この中のファイル名はos.listdirを↑にくっければ取得できます。(表示が長いので、わざと3個にしています)","metadata":{}},{"cell_type":"code","source":"os.listdir(os.path.join(train[\"path\"].iloc[0],\"FLAIR\"))[:3]","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:45:09.110787Z","iopub.execute_input":"2021-08-04T14:45:09.111359Z","iopub.status.idle":"2021-08-04T14:45:09.146576Z","shell.execute_reply.started":"2021-08-04T14:45:09.111315Z","shell.execute_reply":"2021-08-04T14:45:09.145442Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"3. ファイルの数はこれにlenをつければOKです。","metadata":{}},{"cell_type":"code","source":"len(os.listdir(os.path.join(train[\"path\"].iloc[0],\"FLAIR\")))","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:45:09.607949Z","iopub.execute_input":"2021-08-04T14:45:09.608342Z","iopub.status.idle":"2021-08-04T14:45:09.615605Z","shell.execute_reply.started":"2021-08-04T14:45:09.608305Z","shell.execute_reply":"2021-08-04T14:45:09.614642Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"4. ↑のコードの\"FLAIR\"のところは、Scans[0]なので、置き換えて、for文で回します。また、0行目のところはリスト内包を使って振ると、以下の一文で全部DataFrameに収納できます。","metadata":{}},{"cell_type":"code","source":"for scan in Scans:\n    train[scan +\"_count\"] = [ len(os.listdir(os.path.join(train[\"path\"].iloc[s],scan))) for s in tqdm(range(len(train))) ]\n\n","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:45:10.098179Z","iopub.execute_input":"2021-08-04T14:45:10.098791Z","iopub.status.idle":"2021-08-04T14:46:00.743113Z","shell.execute_reply.started":"2021-08-04T14:45:10.098754Z","shell.execute_reply":"2021-08-04T14:46:00.741967Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.74457Z","iopub.execute_input":"2021-08-04T14:46:00.744876Z","iopub.status.idle":"2021-08-04T14:46:00.765943Z","shell.execute_reply.started":"2021-08-04T14:46:00.744845Z","shell.execute_reply":"2021-08-04T14:46:00.764715Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"同じ枚数のIDもあれば、違うのもあることが確認できます。","metadata":{}},{"cell_type":"markdown","source":"全部同じかの確認","metadata":{}},{"cell_type":"code","source":"allsame = [train[\"FLAIR_count\"].iloc[s] ==   train[\"T1w_count\"].iloc[s] ==train[\"T1wCE_count\"].iloc[s] ==train[\"T2w_count\"].iloc[s] \n          for s in range(len(train))]","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.767685Z","iopub.execute_input":"2021-08-04T14:46:00.767997Z","iopub.status.idle":"2021-08-04T14:46:00.79335Z","shell.execute_reply.started":"2021-08-04T14:46:00.767968Z","shell.execute_reply":"2021-08-04T14:46:00.792265Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train[\"allsame\"] = allsame\ntrain","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.795023Z","iopub.execute_input":"2021-08-04T14:46:00.79536Z","iopub.status.idle":"2021-08-04T14:46:00.822973Z","shell.execute_reply.started":"2021-08-04T14:46:00.79533Z","shell.execute_reply":"2021-08-04T14:46:00.821807Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Trueは1と扱われますので、足すと何個Trueがあるかわかります","metadata":{}},{"cell_type":"code","source":"train[\"allsame\"].sum()","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.824206Z","iopub.execute_input":"2021-08-04T14:46:00.824513Z","iopub.status.idle":"2021-08-04T14:46:00.832697Z","shell.execute_reply.started":"2021-08-04T14:46:00.824483Z","shell.execute_reply":"2021-08-04T14:46:00.83144Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train[\"allsame\"].sum()/len(train) * 100","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.83452Z","iopub.execute_input":"2021-08-04T14:46:00.835181Z","iopub.status.idle":"2021-08-04T14:46:00.846788Z","shell.execute_reply.started":"2021-08-04T14:46:00.835127Z","shell.execute_reply":"2021-08-04T14:46:00.845613Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"585の患者idで、63患者Idが同じ枚数あることが確認された（約10%)。\n\n","metadata":{}},{"cell_type":"markdown","source":"## 2.4 画像数がそろっている人の画像を見て理解を深める\n\nわかりやすくイメージするために、全部画像がそろっている人を\n\n試しに、メチル化がある人 1　と　ない人 0の画像を並べて見てみましょう。\n","metadata":{}},{"cell_type":"code","source":"train[train[\"allsame\"]]","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.848756Z","iopub.execute_input":"2021-08-04T14:46:00.849321Z","iopub.status.idle":"2021-08-04T14:46:00.878147Z","shell.execute_reply.started":"2021-08-04T14:46:00.849269Z","shell.execute_reply":"2021-08-04T14:46:00.877151Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"64行目のID100番の人(脳腫瘍である人)と、\n65行目のID102番の人(そうでない人)の画像を全部見てみます。\n\nまずは64行目の人をやって、関数化して65行目の人を見ます。","metadata":{}},{"cell_type":"code","source":"row_ID = 64","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.881631Z","iopub.execute_input":"2021-08-04T14:46:00.882025Z","iopub.status.idle":"2021-08-04T14:46:00.886344Z","shell.execute_reply.started":"2021-08-04T14:46:00.881978Z","shell.execute_reply":"2021-08-04T14:46:00.885223Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train[\"BraTS21ID\"].iloc[row_ID]","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.888977Z","iopub.execute_input":"2021-08-04T14:46:00.889449Z","iopub.status.idle":"2021-08-04T14:46:00.903487Z","shell.execute_reply.started":"2021-08-04T14:46:00.8894Z","shell.execute_reply":"2021-08-04T14:46:00.902565Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"temp_folder = train[\"path\"].iloc[row_ID]\ntemp_folder","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.904883Z","iopub.execute_input":"2021-08-04T14:46:00.905233Z","iopub.status.idle":"2021-08-04T14:46:00.919734Z","shell.execute_reply.started":"2021-08-04T14:46:00.905193Z","shell.execute_reply":"2021-08-04T14:46:00.918619Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"pathをリスト化しちゃいます.まずはFLAIRで。","metadata":{}},{"cell_type":"code","source":"temp_folder2 = os.path.join(temp_folder,\"FLAIR\")\ntemp_files = os.listdir(temp_folder2)\ntemp_files[:3]","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.921155Z","iopub.execute_input":"2021-08-04T14:46:00.921481Z","iopub.status.idle":"2021-08-04T14:46:00.937667Z","shell.execute_reply.started":"2021-08-04T14:46:00.921449Z","shell.execute_reply":"2021-08-04T14:46:00.936453Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"あとで並び替えがきちんとできるようにここで、ファイル名の数字を取っておきます。","metadata":{}},{"cell_type":"code","source":"imagenum = [s.split(\"-\")[1] for s in temp_files]\nimagenum = [s.split(\".\")[0] for s in imagenum]\nimagenum[:3]","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.939236Z","iopub.execute_input":"2021-08-04T14:46:00.939593Z","iopub.status.idle":"2021-08-04T14:46:00.948608Z","shell.execute_reply.started":"2021-08-04T14:46:00.939561Z","shell.execute_reply":"2021-08-04T14:46:00.947491Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"dcmのパスを出します","metadata":{}},{"cell_type":"code","source":"temp_path = [os.path.join(temp_folder2,s) for s in temp_files]\ntemp_path[:3]","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.950317Z","iopub.execute_input":"2021-08-04T14:46:00.951151Z","iopub.status.idle":"2021-08-04T14:46:00.96818Z","shell.execute_reply.started":"2021-08-04T14:46:00.951104Z","shell.execute_reply":"2021-08-04T14:46:00.967247Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"dataframeにして並び替えます。","metadata":{}},{"cell_type":"code","source":"tempdf = pd.DataFrame()\ntempdf[\"image_num\"] = imagenum\ntempdf[\"image_num\"] = tempdf[\"image_num\"].astype(\"int\")\n\ntempdf[\"temp_path\"] = temp_path","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.969696Z","iopub.execute_input":"2021-08-04T14:46:00.970347Z","iopub.status.idle":"2021-08-04T14:46:00.98242Z","shell.execute_reply.started":"2021-08-04T14:46:00.970301Z","shell.execute_reply":"2021-08-04T14:46:00.981238Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"image_numを使ってきれいに、並び替えます。↑でint型にして数字にすることが重要。下の絵のように、よくある1.dcm　→　10.dcmみたいに並ぶと時系列が崩れるため\n\n![image.png](attachment:1fdae302-8cb5-4ac9-8f3d-4305cfcdf9ff.png)","metadata":{},"attachments":{"1fdae302-8cb5-4ac9-8f3d-4305cfcdf9ff.png":{"image/png":"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"}}},{"cell_type":"code","source":"tempdf.head(3)","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.983873Z","iopub.execute_input":"2021-08-04T14:46:00.9842Z","iopub.status.idle":"2021-08-04T14:46:00.997378Z","shell.execute_reply.started":"2021-08-04T14:46:00.984169Z","shell.execute_reply":"2021-08-04T14:46:00.996376Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"tempdf = tempdf.sort_values(\"image_num\").reset_index(drop=True)\ntempdf.head(3)","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:00.998595Z","iopub.execute_input":"2021-08-04T14:46:00.999187Z","iopub.status.idle":"2021-08-04T14:46:01.016607Z","shell.execute_reply.started":"2021-08-04T14:46:00.999137Z","shell.execute_reply":"2021-08-04T14:46:01.015406Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"finpathに収納。","metadata":{}},{"cell_type":"code","source":"finpath = tempdf[\"temp_path\"]","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:01.017659Z","iopub.execute_input":"2021-08-04T14:46:01.017948Z","iopub.status.idle":"2021-08-04T14:46:01.029268Z","shell.execute_reply.started":"2021-08-04T14:46:01.017917Z","shell.execute_reply":"2021-08-04T14:46:01.02808Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"これらを関数化(関数は長く見えますが、↑の64行目の人のコードをここまでコピーして、FLAIRをscanという表現にしただけ)します。\nScansのリストをfor文で回して、これでFLAIR以外も一気に出します","metadata":{}},{"cell_type":"code","source":"def makepath(row_ID,scan):\n    \n    temp_folder = train[\"path\"].iloc[row_ID]\n    temp_folder2 = os.path.join(temp_folder,scan)\n    temp_files = os.listdir(temp_folder2)\n    imagenum = [s.split(\"-\")[1] for s in temp_files]\n    imagenum = [s.split(\".\")[0] for s in imagenum]\n    temp_path = [os.path.join(temp_folder2,s) for s in temp_files]\n    tempdf = pd.DataFrame()\n    tempdf[\"image_num\"] = imagenum\n    tempdf[\"image_num\"] = tempdf[\"image_num\"].astype(\"int\")\n    tempdf[\"temp_path\"] = temp_path\n    tempdf = tempdf.sort_values(\"image_num\").reset_index(drop=True)\n    finpath = tempdf[\"temp_path\"]\n    return finpath","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:01.030834Z","iopub.execute_input":"2021-08-04T14:46:01.031275Z","iopub.status.idle":"2021-08-04T14:46:01.041895Z","shell.execute_reply.started":"2021-08-04T14:46:01.03123Z","shell.execute_reply":"2021-08-04T14:46:01.040962Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"Scans","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:01.043527Z","iopub.execute_input":"2021-08-04T14:46:01.044251Z","iopub.status.idle":"2021-08-04T14:46:01.057246Z","shell.execute_reply.started":"2021-08-04T14:46:01.044197Z","shell.execute_reply":"2021-08-04T14:46:01.056119Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"row Id の一覧を作成(同じ数とわかっているからdataframe化できる。他はできない)","metadata":{}},{"cell_type":"code","source":"row_id=64\n\nsampledf = pd.DataFrame()\nfor scan in Scans:\n    sampledf[scan + \"_path\"] = makepath(row_id,scan)","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:01.05971Z","iopub.execute_input":"2021-08-04T14:46:01.060066Z","iopub.status.idle":"2021-08-04T14:46:01.087111Z","shell.execute_reply.started":"2021-08-04T14:46:01.059997Z","shell.execute_reply":"2021-08-04T14:46:01.085954Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sampledf.head(3)","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:01.088851Z","iopub.execute_input":"2021-08-04T14:46:01.0892Z","iopub.status.idle":"2021-08-04T14:46:01.1023Z","shell.execute_reply.started":"2021-08-04T14:46:01.089169Z","shell.execute_reply":"2021-08-04T14:46:01.101174Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## **MGMT_value=1の人**\n\n(遺伝子にメチル化がある人 = 化学療法に対する反応性の好ましい予後因子および強力な予測因子がある人)の画像表示","metadata":{}},{"cell_type":"code","source":"print(\"MGMT_value = \" + str(train[\"MGMT_value\"].iloc[row_id]))\n\n\nfor row in range(len(sampledf)):\n    plt.figure(figsize=(80,10))\n    for num,scan in enumerate(Scans):\n        img = makeimg(sampledf[scan + \"_path\"].iloc[row])\n        plt.subplot(4,25,num+1)\n        #plt.axis(\"off\")\n        plt.imshow(img)\n        \n        if row==0:\n            plt.title(scan,fontsize=18)\n        if num==0:\n            plt.ylabel(\"row=\" + str(row),fontsize=18)\n\n        ","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:01.10344Z","iopub.execute_input":"2021-08-04T14:46:01.103878Z","iopub.status.idle":"2021-08-04T14:46:13.854184Z","shell.execute_reply.started":"2021-08-04T14:46:01.103843Z","shell.execute_reply":"2021-08-04T14:46:13.853192Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"FLAIRなどは同じ位置を取っているが、見え方が違うことがわかる。\n\n![image.png](attachment:a1b7915a-e4e5-49b4-a4dd-8ef16de718bb.png)\n\nこれの右上あたりが、特徴的なので、メチル化しているのかなと推測します。","metadata":{},"attachments":{"a1b7915a-e4e5-49b4-a4dd-8ef16de718bb.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"## **MGMT_value=0の人\n\n(遺伝子にメチル化がない人 = 化学療法に対する反応性の好ましい予後因子および強力な予測因子がない人)**の画像表示","metadata":{}},{"cell_type":"code","source":"row_id = 65\n\nsampledf = pd.DataFrame()\nfor scan in Scans:\n    sampledf[scan + \"_path\"] = makepath(row_id,scan)\n\nprint(\"MGMT_value = \" + str(train[\"MGMT_value\"].iloc[row_id]))\n\nfor row in range(len(sampledf)):\n    plt.figure(figsize=(80,10))\n    for num,scan in enumerate(Scans):\n        img = makeimg(sampledf[scan + \"_path\"].iloc[row])\n        plt.subplot(4,25,num+1)\n        #plt.axis(\"off\")\n        plt.imshow(img)\n        \n        if row==0:\n            plt.title(scan,fontsize=18)\n        if num==0:\n            plt.ylabel(\"row=\" + str(row),fontsize=18)\n\n        ","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2021-08-04T14:46:13.859817Z","iopub.execute_input":"2021-08-04T14:46:13.860163Z","iopub.status.idle":"2021-08-04T14:46:27.35264Z","shell.execute_reply.started":"2021-08-04T14:46:13.860131Z","shell.execute_reply":"2021-08-04T14:46:27.351208Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"この辺↓は怪しいけど、この人は0なので、メチル化は見つからない。全体的にも怪しいところは少ない。これらの情報からテストデータも見ていくのだと推測。\n\n![image.png](attachment:d030383d-4fe2-43fd-81d2-80ae6e083bf2.png)","metadata":{},"attachments":{"d030383d-4fe2-43fd-81d2-80ae6e083bf2.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"ぱっと見の感覚ですが、最初の方と最後の方は真っ暗だったりするから、何枚かピックアップするなら真ん中くらいの方がいいかもしれませんね。","metadata":{}},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 2.5 各スキャンのファイル数がそろっていない時 (これが約90%)","metadata":{}},{"cell_type":"markdown","source":"データの数が４種類でそろっていないとき、時系列的に数字は同じなのか ? それとも単なる連番なのか ?\nid = 0番の人を見てみます","metadata":{}},{"cell_type":"code","source":"train","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:27.354771Z","iopub.execute_input":"2021-08-04T14:46:27.355249Z","iopub.status.idle":"2021-08-04T14:46:27.377273Z","shell.execute_reply.started":"2021-08-04T14:46:27.355201Z","shell.execute_reply":"2021-08-04T14:46:27.376286Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"ID 0番の人33枚見てみる (T1wの個数が33枚で一番少ないため)","metadata":{}},{"cell_type":"code","source":"row_id = 0\n\nsampledf = pd.DataFrame()\nfor scan in Scans:\n    sampledf[scan + \"_path\"] = makepath(row_id,scan)","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:27.37878Z","iopub.execute_input":"2021-08-04T14:46:27.379122Z","iopub.status.idle":"2021-08-04T14:46:27.414126Z","shell.execute_reply.started":"2021-08-04T14:46:27.379089Z","shell.execute_reply":"2021-08-04T14:46:27.413192Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sampledf","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:27.415277Z","iopub.execute_input":"2021-08-04T14:46:27.415725Z","iopub.status.idle":"2021-08-04T14:46:27.432835Z","shell.execute_reply.started":"2021-08-04T14:46:27.415681Z","shell.execute_reply":"2021-08-04T14:46:27.431625Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sampledf[\"T1w_path\"].iloc[32]","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:27.434361Z","iopub.execute_input":"2021-08-04T14:46:27.434673Z","iopub.status.idle":"2021-08-04T14:46:27.449157Z","shell.execute_reply.started":"2021-08-04T14:46:27.434643Z","shell.execute_reply":"2021-08-04T14:46:27.447425Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"下の方がNanになっていること確認. 番号が若い順に並び変えていて、32行目が33なので、ファイル名は連番","metadata":{}},{"cell_type":"code","source":"print(\"MGMT_value = \" + str(train[\"MGMT_value\"].iloc[row_id]))\n\nfor row in range(33):\n    plt.figure(figsize=(80,5))\n    for num,scan in enumerate(Scans):\n        img = makeimg(sampledf[scan + \"_path\"].iloc[row])\n        plt.subplot(4,33,num+1)\n        #plt.axis(\"off\")\n        plt.imshow(img)\n        \n        if row==0:\n            plt.title(scan,fontsize=18)\n        if num==0:\n            plt.ylabel(\"row=\" + str(row),fontsize=18)\n\n        ","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:46:27.450829Z","iopub.execute_input":"2021-08-04T14:46:27.451284Z","iopub.status.idle":"2021-08-04T14:46:48.435408Z","shell.execute_reply.started":"2021-08-04T14:46:27.451241Z","shell.execute_reply":"2021-08-04T14:46:48.434336Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"T1Wだけ33枚しかないが、明らかにタイミングがずれているので、ファイル名と時間差がありそう。\ndcmファイルから何か他に情報出せるのかも(v13~ 2.6に追記しました)。","metadata":{}},{"cell_type":"markdown","source":"## 2.6 dcmファイルのlocation情報から画像をそろえてみる(v13～)","metadata":{}},{"cell_type":"markdown","source":"https://www.kaggle.com/andradaolteanu/siim-covid-19-box-detect-dcm-metadata\n\nを参照にdcmファイルの中身を見てみる","metadata":{}},{"cell_type":"code","source":"def get_observation_data(path):\n    \"\"\"Get information from the .dcm files.\n    path: complete path to the .dcm file\"\"\"\n\n    image_data = pydicom.read_file(path)\n    \n    # Dictionary to store the information from the image\n    observation_data = {\n        \"FileNumber\" : path.split(\"/\")[5],\n        \"Rows\" : image_data.get(\"Rows\"),\n        \"Columns\" : image_data.get(\"Columns\"),\n        \"PatientID\" : image_data.get(\"PatientID\"),\n        \"BodyPartExamined\" : image_data.get(\"BodyPartExamined\"),\n        \"RotationDirection\" : image_data.get(\"RotationDirection\"),\n        \"ConvolutionKernel\" : image_data.get(\"ConvolutionKernel\"),\n        \"PatientPosition\" : image_data.get(\"PatientPosition\"),\n        \"PhotometricInterpretation\" : image_data.get(\"PhotometricInterpretation\"),\n        \"Modality\" : image_data.get(\"Modality\"),\n        \"StudyInstanceUID\" : image_data.get(\"StudyInstanceUID\"),\n        \"PixelPaddingValue\" : image_data.get(\"PixelPaddingValue\"),\n        \"SamplesPerPixel\" : image_data.get(\"SamplesPerPixel\"),\n        \"BitsAllocated\" : image_data.get(\"BitsAllocated\"),\n        \"BitsStored\" : image_data.get(\"BitsStored\"),\n        \"HighBit\" : image_data.get(\"HighBit\"),\n        \"PixelRepresentation\" : image_data.get(\"PixelRepresentation\"),\n        \"RescaleType\" : image_data.get(\"RescaleType\"),\n    }\n\n    # Integer columns\n    int_columns = [\"SliceThickness\", \"KVP\", \"DistanceSourceToDetector\", \n        \"DistanceSourceToPatient\", \"GantryDetectorTilt\", \"TableHeight\", \n        \"XRayTubeCurrent\", \"GeneratorPower\", \"WindowCenter\", \"WindowWidth\", \n        \"SliceLocation\", \"RescaleIntercept\", \"RescaleSlope\"]\n    for k in int_columns:\n        observation_data[k] = int(image_data.get(k)) if k in image_data else None\n\n    # String columns\n    str_columns = [\"ImagePositionPatient\", \"ImageOrientationPatient\", \"ImageType\", \"PixelSpacing\"]\n    for k in str_columns:\n        observation_data[k] = str(image_data.get(k)) if k in image_data else None\n\n    \n    return observation_data","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:48:26.967926Z","iopub.execute_input":"2021-08-04T14:48:26.968316Z","iopub.status.idle":"2021-08-04T14:48:26.98041Z","shell.execute_reply.started":"2021-08-04T14:48:26.968282Z","shell.execute_reply":"2021-08-04T14:48:26.979195Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"example","metadata":{}},{"cell_type":"code","source":"get_observation_data('../input/rsna-miccai-brain-tumor-radiogenomic-classification/train/00000/FLAIR/Image-20.dcm')","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:48:45.7517Z","iopub.execute_input":"2021-08-04T14:48:45.752152Z","iopub.status.idle":"2021-08-04T14:48:45.771353Z","shell.execute_reply.started":"2021-08-04T14:48:45.752116Z","shell.execute_reply":"2021-08-04T14:48:45.77032Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"この中のSliceLocationをtrainの0行目の患者で、各スキャンでそろえてみます。","metadata":{}},{"cell_type":"markdown","source":"1. 最も画像がたくさんあるscanのSliceLocationを算出","metadata":{}},{"cell_type":"code","source":"Scans","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:50:06.42595Z","iopub.execute_input":"2021-08-04T14:50:06.426494Z","iopub.status.idle":"2021-08-04T14:50:06.432386Z","shell.execute_reply.started":"2021-08-04T14:50:06.426459Z","shell.execute_reply":"2021-08-04T14:50:06.431232Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"Scancount = [s + \"_count\" for s in Scans]\nScancount","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:50:12.396557Z","iopub.execute_input":"2021-08-04T14:50:12.397145Z","iopub.status.idle":"2021-08-04T14:50:12.404095Z","shell.execute_reply.started":"2021-08-04T14:50:12.397094Z","shell.execute_reply":"2021-08-04T14:50:12.403178Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"master = train[Scancount].iloc[0].idxmax()\nmasterpath = makepath(0,master.split(\"_\")[0])\nmasterloc = [get_observation_data(masterpath[b])[\"SliceLocation\"] for b in range(len(masterpath))]\nmasterloc[:10]","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:50:15.211153Z","iopub.execute_input":"2021-08-04T14:50:15.211724Z","iopub.status.idle":"2021-08-04T14:50:19.353833Z","shell.execute_reply.started":"2021-08-04T14:50:15.211676Z","shell.execute_reply":"2021-08-04T14:50:19.35256Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"2. 各pathとlocationの関係を取得","metadata":{}},{"cell_type":"code","source":"sdict = []\nfor a in Scans:\n    path = makepath(0,a)\n    scanloc = [get_observation_data(path[b])[\"SliceLocation\"] for b in range(len(path))]\n    scandict = dict(zip(scanloc,path))\n    sdict.append(scandict)","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:50:44.573305Z","iopub.execute_input":"2021-08-04T14:50:44.573724Z","iopub.status.idle":"2021-08-04T14:50:51.05048Z","shell.execute_reply.started":"2021-08-04T14:50:44.57369Z","shell.execute_reply":"2021-08-04T14:50:51.049543Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"example : Scans[0]　のlocation -88","metadata":{}},{"cell_type":"code","source":"sdict[0][-88]","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:51:49.92051Z","iopub.execute_input":"2021-08-04T14:51:49.920871Z","iopub.status.idle":"2021-08-04T14:51:49.927027Z","shell.execute_reply.started":"2021-08-04T14:51:49.920837Z","shell.execute_reply":"2021-08-04T14:51:49.926084Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"3. 画像が一番多かったscanのlocationをmasterlocとしてdataFrame作成","metadata":{}},{"cell_type":"code","source":"masterdf = pd.DataFrame(masterloc,columns=[\"masterloc\"])\nmasterdf.head(5)","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:52:28.152319Z","iopub.execute_input":"2021-08-04T14:52:28.152706Z","iopub.status.idle":"2021-08-04T14:52:28.164608Z","shell.execute_reply.started":"2021-08-04T14:52:28.152668Z","shell.execute_reply":"2021-08-04T14:52:28.163477Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"4. 重複削除 ( 同じlocationの画像があるみたい )","metadata":{}},{"cell_type":"code","source":"masterdf = masterdf.drop_duplicates().reset_index(drop=True)\nmasterdf","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:53:06.608701Z","iopub.execute_input":"2021-08-04T14:53:06.609347Z","iopub.status.idle":"2021-08-04T14:53:06.628257Z","shell.execute_reply.started":"2021-08-04T14:53:06.609295Z","shell.execute_reply":"2021-08-04T14:53:06.627064Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"5. 各scanごとに対応箇所のパスを展開","metadata":{}},{"cell_type":"code","source":"for num,scan in enumerate(Scans):\n    masterdf[scan] = masterdf[\"masterloc\"].map(sdict[num])","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:53:45.562233Z","iopub.execute_input":"2021-08-04T14:53:45.562602Z","iopub.status.idle":"2021-08-04T14:53:45.574412Z","shell.execute_reply.started":"2021-08-04T14:53:45.56257Z","shell.execute_reply":"2021-08-04T14:53:45.573233Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"masterdf","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:53:52.028916Z","iopub.execute_input":"2021-08-04T14:53:52.029575Z","iopub.status.idle":"2021-08-04T14:53:52.048692Z","shell.execute_reply.started":"2021-08-04T14:53:52.029522Z","shell.execute_reply":"2021-08-04T14:53:52.047507Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"6. nanデータの行削除","metadata":{}},{"cell_type":"code","source":"masterdf=masterdf.dropna(how=\"any\")\nmasterdf = masterdf.reset_index(drop=True)","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:54:29.419491Z","iopub.execute_input":"2021-08-04T14:54:29.420066Z","iopub.status.idle":"2021-08-04T14:54:29.427621Z","shell.execute_reply.started":"2021-08-04T14:54:29.420019Z","shell.execute_reply":"2021-08-04T14:54:29.42664Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"masterdf","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:54:36.016637Z","iopub.execute_input":"2021-08-04T14:54:36.017197Z","iopub.status.idle":"2021-08-04T14:54:36.033803Z","shell.execute_reply.started":"2021-08-04T14:54:36.017158Z","shell.execute_reply":"2021-08-04T14:54:36.032497Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"7. 患者情報、MGMT_valueを追記","metadata":{}},{"cell_type":"code","source":"masterdf[\"BraTS21ID\"]=train[\"BraTS21ID\"].iloc[0]\nmasterdf[\"MGMT_value\"]=train[\"MGMT_value\"].iloc[0]\n","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:56:09.424578Z","iopub.execute_input":"2021-08-04T14:56:09.424955Z","iopub.status.idle":"2021-08-04T14:56:09.431504Z","shell.execute_reply.started":"2021-08-04T14:56:09.424919Z","shell.execute_reply":"2021-08-04T14:56:09.430328Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"masterdf","metadata":{"execution":{"iopub.status.busy":"2021-08-04T14:56:09.615676Z","iopub.execute_input":"2021-08-04T14:56:09.616054Z","iopub.status.idle":"2021-08-04T14:56:09.635755Z","shell.execute_reply.started":"2021-08-04T14:56:09.616003Z","shell.execute_reply":"2021-08-04T14:56:09.634383Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"1-7を関数化(コピーして、0をイメージ番号に変えただけ)","metadata":{}},{"cell_type":"code","source":"def making_loc_path(row):\n    \n\n    master = train[Scancount].iloc[row].idxmax()\n    masterpath = makepath(row,master.split(\"_\")[0])\n    masterloc = [get_observation_data(masterpath[b])[\"SliceLocation\"] for b in range(len(masterpath))]\n\n    sdict = []\n    for a in Scans:\n        path = makepath(row,a)\n        scanloc = [get_observation_data(path[b])[\"SliceLocation\"] for b in range(len(path))]\n        scandict = dict(zip(scanloc,path))\n        sdict.append(scandict)\n\n    masterdf = pd.DataFrame(masterloc,columns=[\"masterloc\"])\n\n    for num,scan in enumerate(Scans):\n        masterdf[scan] = masterdf[\"masterloc\"].map(sdict[num])\n\n\n    masterdf =masterdf.dropna(how=\"any\")\n\n    masterdf = masterdf.drop_duplicates()\n    masterdf = masterdf.reset_index(drop=True)\n    \n        \n    masterdf[\"BraTS21ID\"]=int(train[\"BraTS21ID\"].iloc[row])\n    masterdf[\"MGMT_value\"]=int(train[\"MGMT_value\"].iloc[row])\n\n    \n    return masterdf\n","metadata":{"execution":{"iopub.status.busy":"2021-08-04T15:15:44.360865Z","iopub.execute_input":"2021-08-04T15:15:44.361405Z","iopub.status.idle":"2021-08-04T15:15:44.372731Z","shell.execute_reply.started":"2021-08-04T15:15:44.361369Z","shell.execute_reply":"2021-08-04T15:15:44.371531Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"試しに先ほどの0行目の画像を見てみる","metadata":{"execution":{"iopub.status.busy":"2021-08-04T15:01:40.565954Z","iopub.execute_input":"2021-08-04T15:01:40.56652Z","iopub.status.idle":"2021-08-04T15:01:40.583027Z","shell.execute_reply.started":"2021-08-04T15:01:40.56647Z","shell.execute_reply":"2021-08-04T15:01:40.581555Z"}}},{"cell_type":"code","source":"train[train.index==0]","metadata":{"execution":{"iopub.status.busy":"2021-08-04T15:28:17.353311Z","iopub.execute_input":"2021-08-04T15:28:17.353702Z","iopub.status.idle":"2021-08-04T15:28:17.368318Z","shell.execute_reply.started":"2021-08-04T15:28:17.353673Z","shell.execute_reply":"2021-08-04T15:28:17.36717Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"vi = making_loc_path(0)\nvi","metadata":{"execution":{"iopub.status.busy":"2021-08-04T15:28:23.694605Z","iopub.execute_input":"2021-08-04T15:28:23.694973Z","iopub.status.idle":"2021-08-04T15:28:27.825663Z","shell.execute_reply.started":"2021-08-04T15:28:23.694943Z","shell.execute_reply":"2021-08-04T15:28:27.824376Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## 2.7 Visualization","metadata":{}},{"cell_type":"code","source":"\nfor row in range(len(vi)):\n    plt.figure(figsize=(80,5))\n    for num,scan in enumerate(Scans):\n        img = makeimg(vi[scan].iloc[row])\n        plt.subplot(4,len(vi),num+1)\n        #plt.axis(\"off\")\n        plt.imshow(img)\n        \n        if row==0:\n            plt.title(scan,fontsize=18)\n        if num==0:\n            plt.ylabel(\"loc=\" + str(vi[\"masterloc\"].iloc[row]),fontsize=18)\n\n        ","metadata":{"execution":{"iopub.status.busy":"2021-08-04T15:28:31.900126Z","iopub.execute_input":"2021-08-04T15:28:31.900624Z","iopub.status.idle":"2021-08-04T15:28:43.49032Z","shell.execute_reply.started":"2021-08-04T15:28:31.900591Z","shell.execute_reply":"2021-08-04T15:28:43.489283Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"T2wのスキャン向きが違う気もするが、場所としては合っていそうな気がする。","metadata":{}},{"cell_type":"markdown","source":"別の例で、T2wのスキャン方向がそろっていたもの。560行目","metadata":{}},{"cell_type":"code","source":"train[train.index==560]","metadata":{"execution":{"iopub.status.busy":"2021-08-04T15:30:40.67021Z","iopub.execute_input":"2021-08-04T15:30:40.670604Z","iopub.status.idle":"2021-08-04T15:30:40.685192Z","shell.execute_reply.started":"2021-08-04T15:30:40.670569Z","shell.execute_reply":"2021-08-04T15:30:40.683828Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"vi = making_loc_path(560)\nvi","metadata":{"execution":{"iopub.status.busy":"2021-08-04T15:30:16.75003Z","iopub.execute_input":"2021-08-04T15:30:16.750434Z","iopub.status.idle":"2021-08-04T15:30:17.229253Z","shell.execute_reply.started":"2021-08-04T15:30:16.75039Z","shell.execute_reply":"2021-08-04T15:30:17.227928Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"for row in range(len(vi)):\n    plt.figure(figsize=(80,5))\n    for num,scan in enumerate(Scans):\n        img = makeimg(vi[scan].iloc[row])\n        plt.subplot(4,len(vi),num+1)\n        #plt.axis(\"off\")\n        plt.imshow(img)\n        \n        if row==0:\n            plt.title(scan,fontsize=18)\n        if num==0:\n            plt.ylabel(\"loc=\" + str(vi[\"masterloc\"].iloc[row]),fontsize=18)\n\n        ","metadata":{"execution":{"iopub.status.busy":"2021-08-04T15:30:59.989974Z","iopub.execute_input":"2021-08-04T15:30:59.99034Z","iopub.status.idle":"2021-08-04T15:31:08.2296Z","shell.execute_reply.started":"2021-08-04T15:30:59.990309Z","shell.execute_reply":"2021-08-04T15:31:08.228608Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"合っていそうなことを確認。T2wのスキャン方向はこれは他とそろっているので、種類があるのは気になります。","metadata":{}},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 3. テストデータ\n\n## 3.1 Scanごとの画像数がどれくらい同じなのか確認。","metadata":{}},{"cell_type":"markdown","source":"コードは基本trainと同じなので、まとめてしまいます。","metadata":{}},{"cell_type":"code","source":"sample[\"imfolder\"] = ['{0:05d}'.format(s) for s in sample[\"BraTS21ID\"]]\n\ntest_path = \"../input/rsna-miccai-brain-tumor-radiogenomic-classification/test\"\n\nsample[\"path\"] = [os.path.join(test_path,s) for s in sample[\"imfolder\"]  ]\n\n\nallres = []\n\nfor scan in Scans:\n    sample[scan +\"_count\"] = [ len(os.listdir(os.path.join(sample[\"path\"].iloc[s],scan))) for s in tqdm(range(len(sample))) ]","metadata":{"execution":{"iopub.status.busy":"2021-07-25T16:13:03.972991Z","iopub.execute_input":"2021-07-25T16:13:03.973515Z","iopub.status.idle":"2021-07-25T16:13:07.32034Z","shell.execute_reply.started":"2021-07-25T16:13:03.973483Z","shell.execute_reply":"2021-07-25T16:13:07.319573Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sample","metadata":{"execution":{"iopub.status.busy":"2021-07-25T16:13:08.04927Z","iopub.execute_input":"2021-07-25T16:13:08.04966Z","iopub.status.idle":"2021-07-25T16:13:08.07285Z","shell.execute_reply.started":"2021-07-25T16:13:08.049626Z","shell.execute_reply":"2021-07-25T16:13:08.071573Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"allsame = [sample[\"FLAIR_count\"].iloc[s] ==   sample[\"T1w_count\"].iloc[s] ==sample[\"T1wCE_count\"].iloc[s] ==sample[\"T2w_count\"].iloc[s] \n          for s in range(len(sample))]\n\nsample[\"allsame\"] = allsame\n\nsample","metadata":{"execution":{"iopub.status.busy":"2021-07-25T16:13:11.338128Z","iopub.execute_input":"2021-07-25T16:13:11.338485Z","iopub.status.idle":"2021-07-25T16:13:11.368824Z","shell.execute_reply.started":"2021-07-25T16:13:11.338456Z","shell.execute_reply":"2021-07-25T16:13:11.368056Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sample[\"allsame\"].sum()","metadata":{"execution":{"iopub.status.busy":"2021-07-25T16:13:12.533033Z","iopub.execute_input":"2021-07-25T16:13:12.533384Z","iopub.status.idle":"2021-07-25T16:13:12.540747Z","shell.execute_reply.started":"2021-07-25T16:13:12.533354Z","shell.execute_reply":"2021-07-25T16:13:12.539343Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sample[\"allsame\"].sum()/len(sample) * 100","metadata":{"execution":{"iopub.status.busy":"2021-07-25T16:13:12.973577Z","iopub.execute_input":"2021-07-25T16:13:12.973939Z","iopub.status.idle":"2021-07-25T16:13:12.981569Z","shell.execute_reply.started":"2021-07-25T16:13:12.97391Z","shell.execute_reply":"2021-07-25T16:13:12.980361Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"testデータも約12%は数がそろっている。","metadata":{}},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 4. Submit\n\nテスト的に何か変えて出したい。例えば、画像枚数が同じ場合の傾向を見てみる。","metadata":{}},{"cell_type":"code","source":"train.groupby(\"allsame\")[\"MGMT_value\"].mean().reset_index()","metadata":{"execution":{"iopub.status.busy":"2021-07-25T16:13:15.709208Z","iopub.execute_input":"2021-07-25T16:13:15.709913Z","iopub.status.idle":"2021-07-25T16:13:15.743872Z","shell.execute_reply.started":"2021-07-25T16:13:15.709858Z","shell.execute_reply":"2021-07-25T16:13:15.741995Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"若干の差異がありそうなので、これで出してみます。","metadata":{}},{"cell_type":"code","source":"sample[\"MGMT_value\"] = np.where(sample[\"allsame\"],0.460317,0.532567)","metadata":{"execution":{"iopub.status.busy":"2021-07-25T16:13:16.524172Z","iopub.execute_input":"2021-07-25T16:13:16.52481Z","iopub.status.idle":"2021-07-25T16:13:16.531309Z","shell.execute_reply.started":"2021-07-25T16:13:16.524759Z","shell.execute_reply":"2021-07-25T16:13:16.529963Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sample","metadata":{"execution":{"iopub.status.busy":"2021-07-19T09:03:51.106562Z","iopub.execute_input":"2021-07-19T09:03:51.107032Z","iopub.status.idle":"2021-07-19T09:03:51.124848Z","shell.execute_reply.started":"2021-07-19T09:03:51.107001Z","shell.execute_reply":"2021-07-19T09:03:51.124198Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sample= sample[[\"BraTS21ID\",\"MGMT_value\"]]","metadata":{"execution":{"iopub.status.busy":"2021-07-19T09:03:59.746585Z","iopub.execute_input":"2021-07-19T09:03:59.747061Z","iopub.status.idle":"2021-07-19T09:03:59.751789Z","shell.execute_reply.started":"2021-07-19T09:03:59.74703Z","shell.execute_reply":"2021-07-19T09:03:59.751181Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sample.to_csv(\"submission.csv\",index=False)","metadata":{"execution":{"iopub.status.busy":"2021-07-19T09:04:00.540917Z","iopub.execute_input":"2021-07-19T09:04:00.541264Z","iopub.status.idle":"2021-07-19T09:04:00.549189Z","shell.execute_reply.started":"2021-07-19T09:04:00.541234Z","shell.execute_reply":"2021-07-19T09:04:00.548413Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sample","metadata":{"execution":{"iopub.status.busy":"2021-07-19T09:04:01.485614Z","iopub.execute_input":"2021-07-19T09:04:01.486182Z","iopub.status.idle":"2021-07-19T09:04:01.498599Z","shell.execute_reply.started":"2021-07-19T09:04:01.486091Z","shell.execute_reply":"2021-07-19T09:04:01.497491Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 最後まで見ていただいてありがとうございます。\n\n※以前も私のnotebookにupvoteしてくれた方ありがとうございます。\n\n# お役に立てば、**upvote**いただけたら嬉しいです！\n\n* 最初の方はこのコンペティションは脳腫瘍ある・なしと間違って解釈していました。English版で訂正いただきました。ありがとうございます。そして、初めの方申し訳ございません。","metadata":{}},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}