ORIGINAL RESEARCH article
Front. Bioeng. Biotechnol.
Sec. Cell and Gene Therapy
Enhanced Stem Cell Image Segmentation by Leveraging Visual Processing Mechanisms
Provisionally accepted
- 1Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, China
- 2Shenzhen Cellauto Automation Co., Ltd；National Engineering Research Center of Foundational Technologies for CGT Industry, Shenzhen, China
- 3National Engineering Research Center of Foundational Technologies for CGT Industry, Shenzhen, China
- 4Harbin Beike Health Technology Co., Ltd., Harbin, China
- 5Harbin Beike Health Technology Co., Ltd, Harbin, China
- 6Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fuzhou, China
- 7Shenzhen Cellauto Automation Co., Ltd., Shenzhen, China
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Background: This study aims to investigate the application of visual information processing mechanisms in the segmentation of stem cell (SC) images. The cognitive principles underlying visual information processing were analyzed, and the limitations of conventional segmentation methods were evaluated using phase-contrast microscopy images of stem cells. Methods: An optimized segmentation method incorporating halo correction was developed to address the limitations of traditional approaches. The performance of the proposed method was experimentally validated and compared with existing techniques. Results: The proposed method achieved segmentation accuracy, recall, precision, and F1-score values of 96.5%, 94.9%, 91.4%, and 93.9%, respectively, outperforming existing approaches. Additionally, the confluency error on the Human Mesenchymal Stem Cells dataset and the C2C12 dataset was 0.07 and 0.05, respectively, indicating superior performance compared to equivalent methods. Conclusion: The findings demonstrate that the proposed method offers enhanced efficacy for stem cell image segmentation tasks.
Keywords: image segmentation, Phase contrast microscope, stem cell image processing, visual information cognitive mechanism, Confluency
Received: 05 Sep 2025; Accepted: 17 Nov 2025.
Copyright: © 2025 Zhang, Wang, Liang, Liu, Hu, An and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Mu-yun Liu, liumuyun_lmy@126.com
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