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add files to extract radiomics features from json files
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@@ -23,7 +23,13 @@ workflows: | |
primaryDescriptorPath: /workflows/TotalSegmentator/Terra/postProcessing/perFrame.wdl | ||
authors: | ||
- name: ImagingDataCommons | ||
email: [email protected] | ||
email: [email protected] | ||
- name: convertRadiomicsJsonToDataframeOnTerra | ||
subclass: WDL | ||
primaryDescriptorPath: /workflows/TotalSegmentator/Terra/postProcessing/convertRadiomicsJsonToDataframe.wdl | ||
authors: | ||
- name: ImagingDataCommons | ||
email: [email protected] | ||
- name: TotalSegmentatortwoVmWorkflowOnSB-CGC | ||
subclass: CWL | ||
primaryDescriptorPath: /workflows/TotalSegmentator/SevenBridges/splitWorkflow/twoVM.cwl | ||
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.github/workflows/convert_radiomics_features_json_to_df.yml
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name: convert-radiomics-features-json-dataframe | ||
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on: | ||
push: | ||
branches: | ||
- "main" | ||
paths: | ||
- ".github/workflows/convert_radiomics_features_json_to_df.yml" | ||
- "workflows/TotalSegmentator/Dockerfiles/convert_radiomics_features_json_to_df/Dockerfile" | ||
tags: | ||
- 'v*' | ||
pull_request: | ||
branches: | ||
- "main" | ||
paths: | ||
- ".github/workflows/convert_radiomics_features_json_to_df.yml" | ||
- "workflows/TotalSegmentator/Dockerfiles/convert_radiomics_features_json_to_df/Dockerfile" | ||
workflow_dispatch: | ||
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jobs: | ||
build: | ||
runs-on: ubuntu-latest | ||
steps: | ||
- name: Checkout code | ||
uses: actions/checkout@v4 | ||
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||
- name: Set up Git | ||
run: | | ||
git config --global user.email "[email protected]" | ||
git config --global user.name "GitHub Actions" | ||
- name: Get Git Commit Hash | ||
id: git-commit-hash | ||
run: | | ||
COMMIT_HASH=$(git rev-parse HEAD) | ||
echo "COMMIT_HASH=$COMMIT_HASH" >> $GITHUB_ENV | ||
- name: Docker meta | ||
id: meta | ||
uses: docker/metadata-action@v5 | ||
with: | ||
images: | | ||
imagingdatacommons/convert_radiomics_features_json_to_df | ||
- name: Login to Docker Hub | ||
if: github.event_name != 'pull_request' | ||
uses: docker/login-action@v3 | ||
with: | ||
username: ${{ secrets.DOCKER_USERNAME }} | ||
password: ${{ secrets.DOCKER_PASSWORD }} | ||
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||
- name: Build and Push Docker image to Docker Hub | ||
if: | ||
uses: docker/build-push-action@v5 | ||
with: | ||
context: . | ||
file: ./workflows/TotalSegmentator/Dockerfiles/convert_radiomics_features_json_to_df/Dockerfile | ||
push: ${{ github.event_name != 'pull_request' }} | ||
tags: ${{ steps.meta.outputs.tags }} | ||
build-args: | | ||
GIT_HASH=${{ env.COMMIT_HASH }} | ||
env: | ||
COMMIT_HASH: ${{ env.COMMIT_HASH }} |
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workflows/TotalSegmentator/Dockerfiles/convert_radiomics_features_json_to_df/Dockerfile
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FROM python@sha256:5b287042a6150052420e6a7fb7c1606b6403740880897ae9610faf434da28693 | ||
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ARG GIT_HASH | ||
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LABEL BASE_DOCKER_IMAGE="python:3.11.2-slim-buster"\ | ||
MAINTAINER="IDC <[email protected]>" \ | ||
GIT_HASH=${GIT_HASH}\ | ||
PATH_TO_DOCKER_FILE="https://github.com/imagingdatacommons/CloudSegmentator/blob/${GIT_HASH}/workflows/TotalSegmentator/Dockerfiles/convert_radiomics_features_json_to_dataframe/Dockerfile"\ | ||
IMAGE_NAME_ON_DOCKERHUB="imagingdatacommons/convert_radiomics_features_json_to_dataframe" | ||
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RUN apt-get update && \ | ||
apt-get install -y --no-install-recommends \ | ||
lz4\ | ||
curl\ | ||
wget\ | ||
&& rm -rf /var/lib/apt/lists/* | ||
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RUN pip3 install --no-cache-dir\ | ||
ipykernel==6.22.0\ | ||
ipython==8.11.0\ | ||
ipywidgets==8.0.5\ | ||
jupyter==1.0.0\ | ||
pandas==1.5.3\ | ||
papermill==2.4.0\ | ||
pyarrow==16.1.0 |
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workflows/TotalSegmentator/Notebooks/postProcessingRadiomicsJsonToDataFrame.ipynb
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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "markdown", | ||
"id": "3e33103f", | ||
"metadata": { | ||
"colab_type": "text", | ||
"id": "view-in-github" | ||
}, | ||
"source": [ | ||
"<a href=\"https://colab.research.google.com/github/vkt1414/CloudSegmentator/blob/feat-convert-raw-radiomics-to-dataframe/workflows/TotalSegmentator/Notebooks/postProcessingRadiomicsJsonToDataFrame.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"id": "kdOyoySwehlv", | ||
"metadata": { | ||
"id": "kdOyoySwehlv" | ||
}, | ||
"source": [ | ||
"## **This notebook converts raw radiomics features in JSON format to a pandas dataframe. It takes the raw radiomics files in lz4 format as input, decompresses them, and flattens them to a dataframe, output a csv.lz4**" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"id": "-LdyuHrrPigD", | ||
"metadata": { | ||
"id": "-LdyuHrrPigD" | ||
}, | ||
"source": [ | ||
"### **Installing Packages**" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 1, | ||
"id": "B5KuCCFhOgpA", | ||
"metadata": { | ||
"id": "B5KuCCFhOgpA" | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"%%capture\n", | ||
"import sys\n", | ||
"if 'google.colab' in sys.modules:\n", | ||
" !sudo apt-get update \\\n", | ||
" && apt-get install -y --no-install-recommends \\\n", | ||
" lz4" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"id": "73LFRISZPn6Q", | ||
"metadata": { | ||
"id": "73LFRISZPn6Q" | ||
}, | ||
"source": [ | ||
"### **Importing Packages**" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 6, | ||
"id": "db4585bb-9bfb-4de3-882a-c7454c7ec3af", | ||
"metadata": { | ||
"id": "db4585bb-9bfb-4de3-882a-c7454c7ec3af" | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"import os\n", | ||
"import sys\n", | ||
"import subprocess\n", | ||
"import json\n", | ||
"import pandas as pd\n", | ||
"from pandas import json_normalize" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"id": "Clrt8j70Pb5a", | ||
"metadata": { | ||
"id": "Clrt8j70Pb5a" | ||
}, | ||
"source": [ | ||
"### **Parameters for papermill**" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 7, | ||
"id": "4527d881", | ||
"metadata": { | ||
"id": "4527d881", | ||
"tags": [ | ||
"parameters" | ||
] | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"if 'google.colab' in sys.modules:\n", | ||
" !wget -q https://github.com/vkt1414/CloudSegmentator/releases/download/test/pyradiomicsRadiomicsFeatures.tar.lz4\n", | ||
" rawJsonRadiomicsFiles=[\"pyradiomicsRadiomicsFeatures.tar.lz4\"]\n" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"id": "efd80612", | ||
"metadata": { | ||
"id": "efd80612" | ||
}, | ||
"source": [ | ||
"### **This is the cell used on cloud, as the file paths are passed to the notebook as a string**" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"id": "557de167", | ||
"metadata": { | ||
"id": "557de167" | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"if not 'google.colab' in sys.modules:\n", | ||
" rawJsonRadiomicsFiles=rawJsonRadiomicsFiles.split(',')" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 4, | ||
"id": "ae662d02", | ||
"metadata": { | ||
"id": "ae662d02" | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"def flatten_json(seriesInstanceUID, radiomics_file_path):\n", | ||
" try:\n", | ||
" with open(radiomics_file_path, 'r', encoding='utf-8', errors='ignore') as f:\n", | ||
" data = json.load(f, strict=False)\n", | ||
" except json.JSONDecodeError as e:\n", | ||
" print(f\"Error decoding JSON: {e}\")\n", | ||
" # Write the file path to the error log\n", | ||
" with open('error_file.txt', 'a') as error_file:\n", | ||
" error_file.write(f\"{radiomics_file_path}\\n\")\n", | ||
" return None \n", | ||
"\n", | ||
" # Create an empty list to store DataFrames\n", | ||
" df_list = []\n", | ||
"\n", | ||
" # Iterate over the items in the dictionary and flatten each to a row\n", | ||
" for organ, properties in data.items():\n", | ||
" # Normalize the nested dictionary\n", | ||
" organ_df = json_normalize(properties)\n", | ||
" # Add SeriesInstanceUID\n", | ||
" organ_df['seriesInstanceUID'] = seriesInstanceUID\n", | ||
" # Add the organ name as a column\n", | ||
" organ_df['organ'] = organ\n", | ||
" # Append the result to the list\n", | ||
" df_list.append(organ_df)\n", | ||
"\n", | ||
" # Concatenate all DataFrames in the list\n", | ||
" df = pd.concat(df_list, ignore_index=True)\n", | ||
"\n", | ||
" return df\n" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"id": "nbzivnkRnb_B", | ||
"metadata": { | ||
"id": "nbzivnkRnb_B" | ||
}, | ||
"source": [ | ||
"### **Convert Radiomics features in JSON to DataFrame, finally to a csv**" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"id": "ZHSbg5CrWX1Q", | ||
"metadata": { | ||
"id": "ZHSbg5CrWX1Q" | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"# Main script to decompress files and flatten JSON\n", | ||
"all_dataframes = [] # List to store all DataFrames\n", | ||
"\n", | ||
"for rawJsonRadiomicsFile in rawJsonRadiomicsFiles:\n", | ||
" # Decompress the LZ4 file and extract the tar file\n", | ||
" !lz4 -d --rm $rawJsonRadiomicsFile -c | tar -xvf -\n", | ||
" # Assuming 'radiomics' is a directory in the current working directory\n", | ||
" for series_folder in os.listdir('radiomics'):\n", | ||
" # The directory name is the seriesInstanceUID\n", | ||
" seriesInstanceUID = series_folder\n", | ||
" for file in os.listdir(os.path.join('radiomics',series_folder)):\n", | ||
" if file.endswith('_raw.json.lz4'):\n", | ||
" # Construct the full file path\n", | ||
" file_path = os.path.join('radiomics',series_folder, file)\n", | ||
" # Decompress the file using the lz4 command\n", | ||
" !lz4 -d --rm $file_path\n", | ||
" # Truncate to get the JSON filename\n", | ||
" json_file_path=file_path[:-4]\n", | ||
" # Flatten the JSON file into a DataFrame\n", | ||
" df = flatten_json(seriesInstanceUID, json_file_path)\n", | ||
" # Add the DataFrame to the list\n", | ||
" all_dataframes.append(df)\n", | ||
" !rm -r radiomics\n", | ||
"\n", | ||
"# Concatenate all DataFrames in the list\n", | ||
"final_df = pd.concat(all_dataframes, ignore_index=True)\n", | ||
"\n", | ||
"# Save the final DataFrame to a CSV file\n", | ||
"final_df.to_parquet('raw_radiomics.parquet', index=False)\n", | ||
"\n" | ||
] | ||
} | ||
], | ||
"metadata": { | ||
"celltoolbar": "Tags", | ||
"colab": { | ||
"include_colab_link": true, | ||
"provenance": [] | ||
}, | ||
"kernelspec": { | ||
"display_name": "Python 3 (ipykernel)", | ||
"language": "python", | ||
"name": "python3" | ||
}, | ||
"language_info": { | ||
"codemirror_mode": { | ||
"name": "ipython", | ||
"version": 3 | ||
}, | ||
"file_extension": ".py", | ||
"mimetype": "text/x-python", | ||
"name": "python", | ||
"nbconvert_exporter": "python", | ||
"pygments_lexer": "ipython3", | ||
"version": "3.9.13" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 5 | ||
} |
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