PI-CAI_reader

PI-CAI_reader is a simple tool that creates dataloaders for the T2W MRI series and the corresponding gland masks of the PI-CAI prostate dataset

Required libraries:

os, cv2, numpy, matplotlib, torch, medpy.io

Files and description:

PI-CAI_reader
│    README.md
│
└─── pi_cai_reader_core
│    │   pre_processing.py  # File containing the functions for the dataset creation
│    │   dataloader.py # Custom torch dataset class
│   
│    PI-CAI_reader.ipynb # Colab/Jupyter notebook testbench

Installation

The PI-CAI_reader can be cloned from here or it can be installed using Python pip tool

• Option 1: Clone the repository and see the demo files in python and notebook folders
• Option 2:
  • Install tool using pip3 install git+https://github.com/itzortzis/PI-CAI_reader.git
  • Import the needed components import pi_cai_reader_core.pre_processing and import pi_cai_reader_core.dataloader

The PI-CAI Challenge dataset:

---

A. Saha, J. J. Twilt, J. S. Bosma, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. J. Fütterer, M. de Rooij, H. Huisman, "Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge", DOI: 10.5281/zenodo.6522364