ELECTRICA
Original Article

Blank Frame and Intensity Variation Distortion Detection and Restoration Pipeline for Phase-Contrast Microscopy Time-Lapse Images

1.

Department of Electrical and Electronics Engineering, Faculty of Engineering, Izmir Democracy University, Izmir, Turkey

2.

Virasoft Inc, New York, USA

3.

Department of Biotechnology and Bioengineering, Izmir Institute of Technology Graduate School of Science and Engineering, Izmir, Turkey

4.

Department of Molecular Biology and Genetics, Izmir Institute of Technology Faculty of Science, Izmir, Turkey

5.

Department of Artificial intelligence and Data Engineering, Istanbul Technical University Informatics Institute, Istanbul, Turkey

ELECTRICA 2024; 24: 60-66
DOI: 10.5152/electrica.2024.23030
Read: 175 Downloads: 99 Published: 09 January 2024

In this study, we propose a preprocessing pipeline for the detection and correction of distorted frames in time-lapse images obtained from phase-contrast microscopy. The proposed pipeline employs the average intensities of frames as a foundational element for the analysis. In order to evaluate the degree of correction required for intensity variance, a normalization technique is applied to the difference between the average intensity of a specific frame and the median average intensity of all frames within the study. Our restoration method increases the histogram similarity between the distorted and non-distorted frames, preserves trans-passing pixels in regions of interest, and mitigates the development of additional distortions. The efficacy of the proposed method was evaluated using 15,395 time-lapse image frames from 27 experiments using our own dataset and 830 time-lapse images from four different experiments obtained from the cell tracking challenge. The results of the validation demonstrate a high degree of numerical and visual accuracy of the proposed pipeline.

Cite this article as: M. Ucar, et al., "Blank frame and intensity variation distortion detection and restoration pipeline for phase-contrast microscopy time-lapse images," Electrica, 24(1), 60-66, 2024.

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EISSN 2619-9831