Electrical Capacitance Tomography of Cell Cultures on a CMOS Microelectrode Array

Electrical capacitance tomography (ECT) can be used to predict information about the interior volume of an object based on measured capacitance at its boundaries. Here, we present a microscale capacitance tomography system with a spatial resolution of 10 microns using an active CMOS microelectrode a...

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Bibliographic Details
Published in:IEEE transactions on biomedical circuits and systems 2024-08, Vol.18 (4), p.799-809
Main Authors: Abdelatty, Manar, Incandela, Joseph, Hu, Kangping, Joshi, Pushkaraj, Larkin, Joseph W., Reda, Sherief, Rosenstein, Jacob K.
Format: Article
Language:English
Subjects:
Biomedical measurement
biosensor
Capacitance
Capacitance measurement
CMOS
deep learning
Image reconstruction
inverse problems
microelectrode array
Permittivity
Sensors
Tomography
transposed convolution
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Summary:Electrical capacitance tomography (ECT) can be used to predict information about the interior volume of an object based on measured capacitance at its boundaries. Here, we present a microscale capacitance tomography system with a spatial resolution of 10 microns using an active CMOS microelectrode array. We introduce a deep learning model for reconstructing 3-D volumes of cell cultures using the boundary capacitance measurements acquired from the sensor array, which is trained using a multi-objective loss function that combines a pixel-wise loss function, a distribution-based loss function, and a region-based loss function to improve model's reconstruction accuracy. The multi-objective loss function enhances the model's reconstruction accuracy by 3.2% compared to training only with a pixel-wise loss function. Compared to baseline computational methods, our model achieves an average of 4.6% improvement on the datasets evaluated. We demonstrate our approach on experimental datasets of bacterial biofilms, showcasing the system's ability to resolve microscopic spatial features of cell cultures in three dimensions. Microscale capacitance tomography can be a low-cost, low-power, label-free tool for 3-D imaging of biological samples.
ISSN:1932-4545
1940-9990
1940-9990
DOI:10.1109/TBCAS.2024.3415360