Automated Quantification of Nuclear Fluorescence Signals Using DAPI Segmentation Masks from QuPath
Abstract
This Python-based pipeline provides automated analysis of fluorescence microscopy images. It processes DAPI-stained nuclei segmented with QuPath and quantifies multi-channel fluorescent signals using adaptive thresholding. The tool is designed for high-throughput analysis of nuclear markers in tissue sections.
Fields of Study & Subjects
Cell Image Analysis Techniques
AI in cancer detection
Medical Image Segmentation Techniques
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 11 January 2026