An Image Processing Approach to Determine the Morphological Changes in Cell Nucleus

Confocal imaging has been a powerful tool for scientists over the decades for visualization of cellular architecture and behavior. However, the quantitative inference drawn from the confocal images typically relies upon image processing. So far many image processing tools are available that can quantify various image parameters and image characteristics i.e., intensity, area, shape, volume, perimeter, etc.. However the success of the existing techniques depends on high picture clarity and efficient noise removal. Now in this regard, lots of scoperemains over the increase of the quality of the native image. Moreover, the existing procedure of image processing fails to quantify morphology distortion properly. Though pattern recognition algorithms can often be used to measure the changes, but is seldom able to provide reliable data when the input elements are taken from a pool of varying diversity. Keeping this perspective in mind, we have developed a MATLAB image analysis program for processing of universal confocal images and quantification of cell shape factors. The confocal images were properly processed for efficient noise removal and then subjected to skeletonization algorithm for quantification of cell nucleus shape change. The program was tested to quantify the nuclear mechanotransduction. The nucleus is a key component of the cell and its shape changes with a change in environment. Scientists have now discovered that such variation leads to altered cellular and nuclear function