Automatic Detection of Mitosis and Nuclei From Cytogenetic Images by CellProfiler Software for Mitotic Index Estimation
| Autor: | Omar García, Marina Di Giorgio, Ivonne Romero, Jorge E. González, Joan Francesc Barquinero, A. Radl |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Mitotic index Computer science Scoring criteria Mitosis Cellular viability Sensitivity and Specificity Pattern Recognition Automated 03 medical and health sciences Software Image Interpretation Computer-Assisted Mitotic Index Radiology Nuclear Medicine and imaging Radiometry Cell Nucleus Microscopy Radiation Radiological and Ultrasound Technology business.industry Public Health Environmental and Occupational Health Reproducibility of Results Pattern recognition General Medicine Biological materials 030104 developmental biology Visual detection Fully automated Biological Assay Artificial intelligence business |
| Zdroj: | Radiation protection dosimetry. 172(1-3) |
| ISSN: | 1742-3406 |
| Popis: | Mitotic Index (MI) estimation expressed as percentage of mitosis plays an important role as quality control endpoint. To this end, MI is applied to check the lot of media and reagents to be used throughout the assay and also to check cellular viability after blood sample shipping, indicating satisfactory/unsatisfactory conditions for the progression of cell culture. The objective of this paper was to apply the CellProfiler open-source software for automatic detection of mitotic and nuclei figures from digitized images of cultured human lymphocytes for MI assessment, and to compare its performance to that performed through semi-automatic and visual detection. Lymphocytes were irradiated and cultured for mitosis detection. Sets of images from cultures were analyzed visually and findings were compared with those using CellProfiler software. The CellProfiler pipeline includes the detection of nuclei and mitosis with 80% sensitivity and more than 99% specificity. We conclude that CellProfiler is a reliable tool for counting mitosis and nuclei from cytogenetic images, saves considerable time compared to manual operation and reduces the variability derived from the scoring criteria of different scorers. The CellProfiler automated pipeline achieves good agreement with visual counting workflow, i.e. it allows fully automated mitotic and nuclei scoring in cytogenetic images yielding reliable information with minimal user intervention. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|