End-to-end Python CT volume preprocessing pipeline to convert raw DICOMs into clean 3D numpy arrays for ML. From paper Draelos et al. "Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest Computed Tomography Volumes."

Detects intracranial hemorrhages from CT scans using a lightweight 3D CNN. Includes DICOM processing, 3D volume creation, preprocessing, and model training using Keras. Based on the RSNA 2025 dataset for medical imaging.