pyMarAI
Keywords: Tumor Spheroid Imaging, Radiopharmacological Treatment Response Assays, Delineation, Cancer, Deep-Learning, Artifical Intelligence, Convolutional Neural Networks, Network model, Graphical User Interface
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.
Publications
Automatic Delineation of Tumor Spheroids in Microscopic Images Using Deep-Learning
Maus J, Nitschke J, Nikulin P, Hofheinz F, Barth M, Lemm S, Richter L, Pietzsch J, Braune A, Ullrich M - ACS Measurement Science Au - 2026
pyMarAI: nnU-Net-based Tumor Spheroids Auto Delineation
Maus J, Nitschke J, Nikulin P, Hofheinz F, Barth M, Lemm S, Richter L, Pietzsch J, Braune A, Ullrich M - Rodare - 2026