Update README.md

README.md

@@ -7,7 +7,33 @@ This repository includes codes relevant to the manuscript "Imaging Clusters of P
 * Equally-contributing authors
 
 ## Imaging Clustering
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+### Software Requirements
+- CaPTk, v1.8.1 (https://cbica.github.io/CaPTk/)
+- Python3 
+- R v4.3
+- MATLAB 2023A (v23.2)
+  - Parallel Computing Toolbox
+  - Statistics and Machine Learning Toolbox
+
+### Hardware Used for this Study
+- CUBIC (HPC Cluster) (https://www.med.upenn.edu/cbica/cubic.html)
+- AWS/EC2 for batch image pre-processing, segmentation, radiomic feature extraction
+
+
+### MRI Pre-processing and Tumor Segmentation:
+- Required MRI sequences: T1, T1CE, T2, FLAIR (ADC optional)
+- Pre-processing using BraTS Pre-processing Pipeline, details explained in: https://cbica.github.io/CaPTk/preprocessing_brats.html
+- Tumor Segmentation, all details provided in: https://github.com/d3b-center/peds-brain-auto-seg-public
+- Skull-stripping to generate a brain mask: https://github.com/d3b-center/peds-brain-auto-skull-strip
+- Image normalization:
+   - run_rescale.py
+- Whole tumor generation:
+   - run_wtmask.py
+- Radiomic feature extraction, using CaPTk v1.8.1: https://cbica.github.io/CaPTk/ht_FeatureExtraction.html;
+  - parameter file for radiomic feature extraction: radiomic_feature_params_20230725.csv
+  - sample batch file: SampleBatchFile.csv
+
+### Clustering:
 
 ## Transcriptomic Analysis
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