ArticleEngineering in life sciences2021
Machine learning-based automated fungal cell counting under a complicated background with ilastik and ImageJ.
Article in Engineering in life sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 15 citations in OpenAlex.
- An Agar-Water-Assisted ODJournal of fungi (Basel, Switzerland) · 2026Article
- An automated workflow for fungal cell counting, cell size and data analysis: enhancing throughput and accuracy with the cell analysis and counting tool using ilastik software (caactus).BMC microbiology · 2026Article
- A Machine Learning Pipeline for Automated Bolus Segmentation and Area Measurement in Swallowing Videofluoroscopy Images of an Infant Pig Model.Dysphagia · 2025Article
- RBPMS inhibits bladder cancer metastasis by downregulating MYC pathway through alternative splicing of ANKRD10.Communications biology · 2025Article
- IDCC-SAM: A Zero-Shot Approach for Cell Counting in Immunocytochemistry Dataset Using the Segment Anything Model.Bioengineering (Basel, Switzerland) · 2025Article
- TRAIP suppresses bladder cancer progression by catalyzing K48-linked polyubiquitination of MYC.Oncogene · 2024Article
- YOLOv5-FPN: A Robust Framework for Multi-Sized Cell Counting in Fluorescence Images.Diagnostics (Basel, Switzerland) · 2023Article
- An Automated Cell Detection Method for TH-positive Dopaminergic Neurons in a Mouse Model of Parkinson's Disease Using Convolutional Neural Networks.Experimental neurobiology · 2023Article
- Machine learning-based automated fungal cell counting under a complicated background with ilastik and ImageJ.Engineering in life sciences · 2021Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Measuring the concentration and viability of fungal cells is an important and fundamental procedure in scientific research and industrial fermentation. In consideration of the drawbacks of manual cell counting, large quantities of fungal cells require methods that provide easy, objective and reproducible high-throughput calculations, especially for samples in complicated backgrounds. To answer this challenge, we explored and developed an easy-to-use fungal cell counting pipeline that combined the machine learning-based ilastik tool with the freeware ImageJ, as well as a conventional photomicroscope. Briefly, learning from labels provided by the user, ilastik performs segmentation and classification automatically in batch processing mode and thus discriminates fungal cells from complex backgrounds. The files processed through ilastik can be recognized by ImageJ, which can compute the numeric results with the macro 'Fungal Cell Counter'. Taking the yeast
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.