A new algorithm for band detection and pattern extraction on pulsed-field gel electrophoresis images
- Published
- Accepted
- Subject Areas
- Computational Biology, Computer Vision, Scientific Computing and Simulation
- Keywords
- Pattern recognition, Image processing, Pulsed-field gel electrophoresis, Band detection
- Copyright
- © 2019 Rezaei et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2019. A new algorithm for band detection and pattern extraction on pulsed-field gel electrophoresis images. PeerJ Preprints 7:e27771v1 https://doi.org/10.7287/peerj.preprints.27771v1
Abstract
This paper presents a new approach for band detection and pattern recognition for molecule types. Although a few studies have examined band detection, but there is still no automatic method that can perform well despite the high noise. The band detection algorithm was designed in two parts, including band location and lane pattern recognition. In order to improve band detection and remove undesirable bands, the shape and light intensity of the bands were used as features. One-hundred lane images were selected for the training stage and 350 lane images for the testing stage to evaluate the proposed algorithm in a random fashion. All the images were prepared using PFGE BIORAD at the Microbiology Laboratory of Kermanshah University of Medical Sciences. An adaptive median filter with a filter size of 5x5 was selected as the optimal filter for removing noise. The results showed that the proposed algorithm has a 98.45% accuracy and is associated with less errors compared to other methods. The proposed algorithm has a good accuracy for band detection in pulsed-field gel electrophoresis images. Considering the shape of the peaks caused by the bands in the vertical projection profile of the signal, this method can reduce band detection errors. To improve accuracy, we recommend that the designed algorithm be examined for other types of molecules as well.
Author Comment
This is a submission to PeerJ Computer Science for review.
