Scientific research, particularly in the fields of biomedicine and the biological sciences, depends heavily on image analysis. This procedure is essential for comprehending and deriving relevant information from the visual data collected in laboratory studies, assisting researchers in formulating valid findings.
Cell biologists need strong and trustworthy image analysis tools to unbiasedly extract the necessary metrics from their images. With this data, the researchers are able to make sense of biological processes that can then be shared with the broader scientific community, ultimately having a great impact on public health and society as a whole.
This article give a brief overview of how microscopy image analysis software is used in cell biology experiments, with a specific focus on the WiSoft Athena system.
Steps of imaging data analysis performed by automated image analysis software. Image Credit: IDEA Bio-Medical Ltd.
Using image analysis software in cell biology experiments
The majority of the research that is conducted to deeply explore and comprehend cell biology is supported by image-based investigations. Scientists can examine cells on microscope samples in greater detail using image analysis software, which enables the assessment of significant, quantitative data on the target cell subjects.
Depending on the research subject, this data may contain details on the physical characteristics of cells and tissues, cell-to-cell interactions, intracellular processes, whole-organism physiology, or even a cell’s dynamics with viral or bacterial agents, such as in the study of diseases.
The use of automated image analysis software enables the simultaneous examination of several pictures based on either single cells or a cell population. Laboratory experimentation is made more efficient by integrating such software with automated microscopes for real-time analysis that runs concurrently with image capture.
A previous post about High Content Imaging (HCI) introduced High Content Analysis (HCA) as it involved the use of automated image analysis software. Computer algorithms that take one or more photographs as input and extract data from objects in those images are under total control of automated image analysis.
These algorithms start by separating photos into items of interest, which are chosen based on particular pixel value characteristics. Fluorescence pictures are appropriate for this research because they have precise labeling and strong contrast.
The potency of fluorescence labeling and the ongoing need to create new fluorescent labels are key aspects that are imparted by the analysis of fluorescence images. In fluorescence images, bright objects of interest are segmented away from the dark background that is ignored.
By observing variations in pixel intensity values, which frequently indicate the borders of objects, transmitted light pictures can also be used to detect structures.
Following segmentation, measurements are taken on each item to derive metrics like statistics on pixel intensity levels and object form and morphology (e.g., area, shape, elongation, etc.). The interaction of objects recognized in several color channels can also be studied using advanced analytic techniques, such as the colocalization of many signals in adjacent areas.
Data obtained using multiple imaging channels can also allow for interpretation of the signals, for example, presence within a cellular location such as the nucleus vs. cytoplasm. It is the impartial nature of automated picture analysis that makes it effective.
Researchers can consistently and dependably apply segmentation criteria to a variety of datasets after they have been identified and configured.
The data produced can be readily compared to one another, provided the experimental setup and imaging circumstances are constant. While some misidentification might occur when using automated methods, with the right controls and sample size, the systematic error that arises can be decreased to produce statistically significant findings.
The reliability of biological differences or changes discovered in this approach is greater than that of manual image analysis, which is always susceptible to the bias of the researcher that is conducting the study.
Using cutting-edge analytic methods, the WiScan® Athena image analysis software can record, measure, and retrieve morphological and intensity-based data from cells. Additionally, the Athena software’s visualization features enable the display of analytic results in a way that is simple to present and share.
Life sciences experiments can be conducted quicker and with fewer resources thanks to the software’s versatility and adaptability to the demands of its customers. This, in turn, allows more time for innovation, creativity, and critical thought around the results being provided by the cutting-edge image analysis software.
Image analysis software solutions with Idea Bio
Being one of the top automated microscopy businesses in the world, IDEA-Bio specializes in automated image analysis software. User demands for image analysis software have been met by the tireless work of their team of scientists, developers, and engineers who have applied their in-depth knowledge of cell research needs to produce solutions.
The program for WiSoft® Athena image analysis shows the results.
Image Credit: IDEA Bio-Medical Ltd.
With the touch of a button, the WiSoft® system provides a simple and rapid interface for the assessment of experimental data. This tool can be used to analyze the most popular cell biology experiments, including protein expression, cell count, cell cycles, intranuclear functions, toxicity, organelle quantification, colocalization, transfection, and many more, in addition to the tasks briefly stated above.
For more information about the WiSoft Athena system and image analysis software options from IDEA-Bio, get in contact with a member of the team. Requesting a demo or sending a message to a member of their knowledgeable team as soon as possible will allow them to handle particular requirements of the user.
About IDEA Bio-Medical Ltd.
IDEA Bio-Medical is founded in 2007 through a partnership between YEDA (the Weizmann Institute’s commercialization arm) and IDEA Machine Development (an innovation hub).
We specialize in automated imaging systems and image analysis software, offering a broad range of biological applications based on the company’s unique algorithms library. The company is developing novel image-based screening platforms for the pharmaceutical industry and medical centers, dedicated to broadening the scope of personalized medicine.
Our WiScan Hermes system incorporates the most advanced technologies currently available in the machine vision field, integrated with engineering methodologies of high reliability and quality at the level of semi-conductors and digital printing industries, which are the specialty of our mother company, IDEA Machine Development Design and Production Ltd.
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