Image Processing of Proteins 3D Images
Abstract
Images are a good source of important and meaningful information. Now days, more efforts have been put to understand and simplify of the 3D objects. Image processing and feature extraction of three 3D images played a key role in understanding proteins structures. There are several techniques has been used to visualize the images of micro atoms, and CryoEm is an experimental techniques, which is capable of visualizing the large molecular complexes such as viruses. Using the current advance techniques of CryoEm, it is possible to produce the 3D gray scale images of a proteins molecule in the high resolution. Computation technique is advantageous on the experimental technique because it can handle larger proteins and work on types of proteins. Experimental techniques only work on mostly in high resolution whereas computational techniques work on medium as well as low resolution. One most important, if other technique fails computational technique works such as membrane proteins. Most of the techniques works on the segmented gray scale images, and approaches on unsegment gray-scale images are very erratic. Most of the methods apply an initial segmentation to remove the less representatives foreground voxels. It is also not possible to retrieve all the information and features of the images. In this paper, we present a computational method to extract the skeleton by using segmentation free approach. To retrieve the skeleton from the 3D density map non-iterative method has been used, and the approach only considers the interior gray- scale image’s intensity of the density map. The proposed algorithm will find the voxels depends on their intensity, and calculates the paths between the voxels. After calculating the paths and local volume peaks we will retrieve the skeleton. This skeleton is more likely to be robust and informative. Visual Studio 2010 C++ has been used to accomplish the task.
Subject Area
Bioinformatics
Recommended Citation
Pankaj Mishra,
"Image Processing of Proteins 3D Images"
(2016).
ETD Collection for Tennessee State University.
Paper AAI10119074.
https://digitalscholarship.tnstate.edu/dissertations/AAI10119074