Automated Method for the Rapid and Precise Estimation of Adherent Cell Culture Characteristics from Phase Contrast Microscopy Images
- Submitting institution
-
University College London
- Unit of assessment
- 12 - Engineering
- Output identifier
- 11842
- Type
- D - Journal article
- DOI
-
10.1002/bit.25115
- Title of journal
- Biotechnology and Bioengineering
- Article number
- -
- First page
- 504
- Volume
- 111
- Issue
- 3
- ISSN
- 0006-3592
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fbit.25115&file=bit25115-sm-0001-SupFig-S1.tif
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
6
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Combined microfluidics, image processing, and spectroscopy for first ever demonstration of label-free, non-invasive, and real-time detection of cell density estimation and of specific oxygen uptake rates of adherent cells. Paper made front cover of journal. Led to numerous oral presentations and keynotes (Lab-on-Chip India 2018; Opening of the new Research Center PVZ at TU Braunschweig, 2017). Attracted industrial interest from MicrofluidX for partnering, won InnovateUK grant (£100k for UCL). Led to follow-on funding of EngD studentship with Aglaris Ltd., Stevenage. Underpinned successful CDT Bioprocess Engineering Leadership application (2018). Led to workshop on Bioprocess Microfluidics at leading microfluidics conference (microTAS, 2018).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
