Malik, Hafizi and Idris, Ahmad Syahrin and Toha @ Tohara, Siti Fauziah and Idris, Izyan Mohd and Daud, Muhammad Fauzi and Tokhi, Mohammad Osman (2023) Deploying patch-based segmentation pipeline for fibroblast cell images at varying magnifications. IEEE Access, 11. pp. 98171-98181. E-ISSN 2169-3536
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Abstract
Cell culture monitoring necessitates thorough attention for the continuous characterization of cultivated cells. Machine learning has recently emerged to engage in a process, such as a microscopy segmentation task; however, the trained data may not be comprehensive for other datasets. Most algorithms do not encompass a wide range of data attributes and require distinct system workflows. Thus, the main objective of the research is to propose a segmentation pipeline specifically for fibroblast cell images on phase contrast microscopy at different magnifications and to achieve reliable predictions during deployment. The research employs patch-based segmentation for predictions, with U-Net as the baseline architecture. The proposed segmentation pipeline demonstrated significant performance for the UNet-based network, achieving an IoU score above 0.7 for multiple magnifications, and provided predictions for cell confluency value with less than 3% error. The study also found that the proposed model could segment the fibroblast cells in under 10 seconds with the help of OpenVINO and Intel Compute Stick 2 on Raspberry Pi, with its optimal precision limited to approximately 80% cell confluency which is sufficient for real-world deployment as the cell culture is typically ready for passaging at the threshold.
| Item Type: | Article (Journal) |
|---|---|
| Uncontrolled Keywords: | Cell confluency, deep learning, fibroblast, microscopy segmentation, phase contrast. |
| Subjects: | T Technology > T Technology (General) > T10.5 Communication of technical information |
| Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Engineering > Department of Mechatronics Engineering Kulliyyah of Engineering |
| Depositing User: | Dr. Siti Fauziah Toha |
| Date Deposited: | 02 Apr 2024 15:18 |
| Last Modified: | 02 Apr 2024 15:18 |
| URI: | http://irep.iium.edu.my/id/eprint/111701 |
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