Software Open Access
pyMarAI: nnU-Net-based Tumor Spheroids Auto Delineation
Maus, Jens;
Nitschke, Janina;
Nikulin, Pavel;
Hofheinz, Frank;
Barth, Mareike;
Lemm, Sandy;
Richter, Lena;
Pietzsch, Jens;
Braune, Anja;
Ullrich, Martin
Collection of neural network models for automatic image segmentation of microscopic tumor spheroids. Intended to be used with nnU-Net deep-learning framework. Trained and tested on a total of microscopic images of mouse pheochromocytoma (MPC) tumor cells.
In addition to the trained network model, a PyQt5-based graphical user interface tool is provided. This tool provides a complete pipeline for handling microscopic spheroid image data, running deep-learning–based delineation, and curating results for continuous model improvement.
For installation and usage instructions, please visit https://github.com/hzdr-MedImaging/pyMarAI
Please cite nnU-Net and the respective paper when using pyMarAI.
List of available model types:
pyMarAI-1.0.0-ecat.zip: nnUNetv2 ready network (for ECAT7)pyMarAI-1.0.0-nifti.zip: nnUNetv2 ready network (for NIFTI)
| Name | Size | |
|---|---|---|
|
pyMarAI-1.0.0-ecat.zip
md5:080c71677fa8fb76699c0fe0fa7b6055 |
771.3 MB | Download |
|
pyMarAI-1.0.0-nifti.zip
md5:fb5bbfab30e23c77542a2fd1eb82132e |
771.3 MB | Download |
| All versions | This version | |
|---|---|---|
| Views | 109 | 109 |
| Downloads | 1 | 1 |
| Data volume | 771.3 MB | 771.3 MB |
| Unique views | 104 | 104 |
| Unique downloads | 1 | 1 |
- Publication date:
- January 7, 2026
- DOI:
-
- Keyword(s):
- Tumor Spheroid Imaging Radiopharmacological Treatment Response Assays Delineation Cancer Deep-Learning Artifical Intelligence Convolutional Neural Networks Network model
- Related identifiers:
- Identical to:
https://www.hzdr.de/publications/Publ-42498 - Referenced by:
https://www.hzdr.de/publications/Publ-42497 - Supplement to:
https://github.com/hzdr-MedImaging/pyMarAI - Communities:
- License (for files):
- Creative Commons Attribution Share Alike 4.0 International