MiroslavKabat / kits19

kits19 🎗️

Demonstration how to get kits19 intersection over union (IOU) above 80 % with 2D UNet using transfer learning!

Raw image	Mask (Ground Truth)	Prediction

Quick start 🎬

• Read challange paper: kits19.grand-challenge.org
• Follow neheller's github to get data a libraries: github
• If you have downloaded data folder including imaging.nii.gz and segmentation.nii.gz in each folder (first 209 only), you can start using my scripts
  • Run sanitycheck.py to create png folder with visualisation of raw data
  • Run convertniitonpz.py to create npz folder with preprocessed images compressed in to *.npz files for fast data loading
  • Run train.py to create models folder with timestamps folders containing TensorBoard, .csv and models!
  • Run predict.py to create models/{timestamp}/predictions with predicted heatmaps in grayscale

Contribution 🤝

Pull Request welcome

Contact 🤙🏻

If you need help with your project, my work helps you or you have any ideas how to improve my code, let me know about it!

👦🏻 www.MiroslavKabat.com

✉️ [e-mail]

Donations ❤️

I spent in this project more like 🕒 16 man-hours with ⌛ 18 months of getting knowledge and 💸 6000 $ for workstation, I appreciate any donations. PayPal Donations Thank you!