APA (7th ed.) Citation

Piotrowski, T., Rippel, O., Elanzew, A., Nießing, B., Stucken, S., Jung, S., . . . Jonas, S. (2021). Deep-learning-based multi-class segmentation for automated, non-invasive routine assessment of human pluripotent stem cell culture status. Computers in biology and medicine, 129, 104172. https://doi.org/10.1016/j.compbiomed.2020.104172

Chicago Style (17th ed.) Citation

Piotrowski, Tobias, et al. "Deep-learning-based Multi-class Segmentation for Automated, Non-invasive Routine Assessment of Human Pluripotent Stem Cell Culture Status." Computers in Biology and Medicine 129 (2021): 104172. https://doi.org/10.1016/j.compbiomed.2020.104172.

MLA (9th ed.) Citation

Piotrowski, Tobias, et al. "Deep-learning-based Multi-class Segmentation for Automated, Non-invasive Routine Assessment of Human Pluripotent Stem Cell Culture Status." Computers in Biology and Medicine, vol. 129, 2021, p. 104172, https://doi.org/10.1016/j.compbiomed.2020.104172.