Automatic Generation of Analog Hardware Description
Language (AHDL) Code from Cell Culture Images
Alberto Yúfera
1
and Estefanía Gallego
2
1
Instituto de Microelectrónica de Sevilla (IMSE), Centro Nacional de Microelectrónica (CNM-CSIC)
Universidad de Sevilla
Av. Américo Vespucio s/n. 41092. Sevilla. SPAIN
e-mail: yufera@imse-cnm.csic.es
2
Dto. Tecnología Electrónica, Universidad de Sevilla
Av. Reina Mercedes s/n. 41022. Sevilla. SPAIN
e-mail: estefania.gallego@gmail.com
Abstract--This paper presents a computer tool for
automatic analysis of cell culture images. The program allows
the extraction of relevant information from biological images
for pre and post system analysis. In particular, this tool is being
used for electrical characterization of electrode-solution-cell
systems in which bio-impedance is the main parameter to be
known. The correct modeling of this kind of systems enables
both electronic system characterization for circuit design
specifications and data decoding from measurements. The
developed program can be used in cell culture image
processing for geographic information extraction and sensor
sizing, generating cell count and Analog Hardware Description
Language (AHDL) equivalent circuits useful for whole system
electrical simulations.
Keywords--Microelectrode; bioimpedance sensor; Analog
Hardware Description Language; image processing.
I. INTRODUCTION
The impedance is a useful parameter for determining the
properties of biological materials for several reasons: first, they are
conductive [1] second, the impedance measurement represents a
non-invasive technique, and third, it is a relatively cheap technique.
Many biological parameters and processes can be sensed and
monitored using its impedance as marker [2-5]. Impedance
Spectroscopy (IS) of cell culture [6] and Electrical Impedance
Tomography (EIT) in bodies [7] are examples of the impedance
utility for measuring biological and medical processes and
parameters. Classical real-time monitoring and imaging systems for
biological samples are based on optical stimulation of samples,
demanding bulky and expensive equipments. Embedded
Complementary Metal-Oxide-Semiconductor (CMOS) sensors have
been reported as an alternative for increasing the sensitivity to cell
location and manipulation. The most popular are optical [9],
capacitive [7] and impedance [8] based sensors. Despite of the high
number of papers with optical sensors the last years, they still need
external lamps, optical fibbers, etc, while capacitive and impedance
based detection do not rely on peripheral equipment.
This paper is related to a new method for impedance
measurement with applications to cell culture systems. The system
in fig. 1 employs a two dimensional electrode array as sensors
[10,11] together with CMOS circuits for impedance measurements
[12]. Microelectronic circuits must be designed to work with
constraints imposed by the electrode sensors. The whole system in
fig. 1 can be fully-integrated in CMOS technologies [10]. When
low concentration cell cultures are carried out on top of the
electrode array, depending on the position of each cell, specific
electrode-cell impedance will be measured, allowing cell detection.
Electrical models reported for the electrode-cell interface
description [11.12] are the key for matching electrical simulations
to real systems performance and hence decoding correctly the
experimental results, usually known as a reconstruction problem.
This kind of system can be used for real-time monitoring of cell
cultures with the Electrical Cell Impedance Spectroscopy technique
(ECIS), [6].
Fig. 1. (a) Simplified system set-up: circuits and 2D electrode sensor array
for bio-impedance measurement. (b) Each sensor has e1 and e2 electrodes.
Cell culture is done on electrode top.
In this paper is presented a computer tool that aids in cell
culture image processing and reconstruction, helping to the
optimization of circuit design since it enables the emulation of
biological loads. In the system shown in fig. 1, the tasks of to be
done are:
To perform a pre-processing of a cell culture image to define
the areas occupied by cells. Digital Image Processing (DIP) is
focused on segmentation to discriminate the total area covered
by cells.
To incorporate the definition of the electrode area. This is
important not only from the electrode-solution-cell system
modeling and characterization point of view; but because the
electrode sensitivity of the impedance sensor will be dependent
of its size and working frequency. The electrode-cell overlap
Image Processing Theory, Tools and Applications
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