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Real-time semantic segmentation and anomaly detection of functional images for cell therapy manufacturing.
- Source :
-
Cytotherapy (Elsevier Inc.) . Dec2023, Vol. 25 Issue 12, p1361-1369. 9p. - Publication Year :
- 2023
-
Abstract
- Cell therapy is a promising treatment method that uses living cells to address a variety of diseases and conditions, including cardiovascular diseases, neurologic disorders and certain cancers. As interest in cell therapy grows, there is a need to shift to a more efficient, scalable and automated manufacturing process that can produce high-quality products at a lower cost. One way to achieve this is using non-invasive imaging and real-time image analysis techniques to monitor and control the manufacturing process. This work presents a machine learning-based image analysis pipeline that includes semantic segmentation and anomaly detection capabilities. This method can be easily implemented even when given a limited dataset of annotated images, is able to segment cells and debris and can identify anomalies such as contamination or hardware failure. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14653249
- Volume :
- 25
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Cytotherapy (Elsevier Inc.)
- Publication Type :
- Academic Journal
- Accession number :
- 173524255
- Full Text :
- https://doi.org/10.1016/j.jcyt.2023.08.011