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Introduction to Biological Image Analysis



In this lab, various techniques for the analysis and quantification of images from wet lab experiments are discussed using Image Analysis software.




  • To study the various techniques applied for analyzing and quantifying biological images.




Image analysis plays an important role in the scientific field due to its wide range of applications in quantitative measurements. Visualization and image analysis methods are critical for understanding various features of cell biology, molecular biology and neuroscience. With the development of fluorescent probes and the application of high-resolution microscopes biological image processing techniques became more reliable with a profound impact on research in the biological sciences.


One of the most important and frequently overlooked aspects of the cell imaging is image quantification and analysis.  In the past, microscopic techniques were applied to study the structural details, but the recent advances in research, demands on determination of the number of cells, its area, perimeter, localization, concentration, densitometry analysis, etc.,. for molecular level studies. Biologists are increasingly interested in using the image analysis protocols to convert the microscopic images into more relatively quantitative measurements.


The difficulties in visual interpretation such as counting of the cell and quantification of specific molecules of interest in the research application, can be overcome by implementing automated methods in these fields. Computerized image analysis has lot of applications over visual analysis, including reproducibility, rapidity, adaptability and the ability to simultaneously measure many features in the image. The goal of image analysis techniques is to combine the results of the wet laboratory techniques with image analysis software, thereby providing more quantitative information.


A large number of image analysis software packages have been developed for biological applications due to their usability in biological sciences. These software packages help to extract useful information from the specimens (image) of interest. In fact, most of this software is expensive and often requires high performance computers to function. Throughout this lab, ImageJ is referred as standard image analysis software, since it is freely available, platform independent and is applicable to the biological researchers to quantify the results obtained in the laboratory techniques.


Applications of Image Analysis Software:


Image analysis software has multiple applications, including the analysis of microscopy, gel, fluorescent stained tissues, and in the medical analysis of specimens obtained from the patient’s sample. Usually, image processing techniques are applied to correct problems such as uneven illumination and to enhance images for further analysis, display, and publication.

Densitometry, that is, the determination of intensity of apparent amounts of a specific molecule at a certain position inside the sample, can be analyzed with the help of the image analysis software. Image analysis software is used compare the bands detected on the gel, for example, in PAGE, AGE, and Western blot, and also to detect the spot developed on the TLC plate.  Here, the image analysis techniques are applied to quantify the endogenous expression of target protein (in case of Western blot and PAGE), presence of DNA in specific regions of the gel, depending on its molecular size (in case of AGE) and to quantify the amount of amino acids present in an unknown sample (in case of TLC). In Western blot, the densitometry analysis can also be applied to find the expression of various proteins, for example, cancer causing proteins, by determining the relative intensity of proteins in the patient’s sample.


In the medical field, image analysis can also be applied to measure or count the nuclear or cytoplasmic stain which can be applied for prognosis, diagnosis and evaluation of response to antibiotic therapies. It can measure differences in staining intensity of a tissue sample.


Quantification of fluorescent images is widely used in molecular biology and biochemistry laboratories for a wide variety of experimental, analytical and quality control applications. In fluorescent microscopes, the image analysis techniques can be used to determine the location of fluorophores in tissue sections that can be applied for the future purposes. The quantification of fluorescence imaging techniques has potential applications in both biomedical research and clinical practices. Moreover, quantitative image analysis of DNA staining with respect to its intensity reveals whether a cell is in G1 or G2 phase of the cell cycle. ImageJ help in the Cell count (used to probe cell proliferation/apoptosis/death) that can be difficult to obtain by manual cell counting processes.


Image analysis can also help to identify the phenotypes, such as shape and texture of the cell of interest, that are not otherwise easily measured. Quantitative measurements of the cell morphology are important in studying the normal cellular physiology and in disease diagnosis. Over all, the accuracy of the information obtained through the analysis software depends not only on the quality of the image, but also on the ability of the analysis software to distinguish the image features from the provided data and to convert it into meaningful measurements.




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