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Code Warriors 2 Approach

3D Image Processing and Analysis

This repository provides tools for preprocessing, training, and prediction using 3D medical images. It includes scripts for configuring, slicing, and analyzing the images to study tissue characteristics.

📂 Repository Structure

  • requirements.txt: Contains the Python dependencies required to run the project.
  • data_utils/make_config.py: Script to generate a configuration file for the preprocessing pipeline.
  • preprocess.py: Preprocesses 3D images based on the generated configuration.
  • train.py: Handles the training of the model using preprocessed data.
  • predict.py: Predicts outcomes using a trained model on new data.
  • data_utils/example_config.json: Example configuration file with default values.

🛠️ Features and Usage

1. Generate a Configuration

Use make_config.py to create a configuration file for your 3D image preprocessing. The configuration includes parameters such as thresholds for cropping and directories for input and output.

Run the script:

python make_config.py

2. Preprocess Images

Preprocess 3D images based on the generated configuration. The preprocessing includes:

Cropping based on tissue content thresholds. Slicing 3D images into smaller 2D representations. Saving processed data and metadata for downstream tasks. Run the script:

python preprocess.py

3.Train the Model

Train your model using the preprocessed data and updated metadata.

Run the script:

python train.py

4. Make Predictions

Use the trained model to predict outcomes on new datasets.

Run the script:

python predict.py