Current image-based methods for monitoring cell confluency are subjective, leading to inconsistencies in cell therapy quality.
A deep neural network was used to analyze images of mesenchymal stem cells from different culture vessels, employing a classification and detection algorithm to assess cell status accurately.
This research is groundbreaking in using deep learning for analyzing cell images, enhancing the yield and quality critical to stem cell therapeutics.