Bio-medical image enhancement using hybrid metaheuristic coupled soft computing tools
Shouvik Chakraborty, Kalyani K Mali, Sankhadeep Chatterjee, Soumen Banerjee, Aayush Sah, Dev S. Pathak, Suparba Nath, Debkumar Singha Roy · 2017
The biomedical image analysis methods are considered to be the effective and important tool for screening, detection and diagnosis. It is nearly inevitable tool and works as the helping hand for physicians. One of the major issues related with the biomedical images is that most of the images (of different modalities) are suffered from noise and other different quality related problems like poor contrast, blurring, and difficulties in extracting suitable information. Therefore it necessary to design some techniques that can enhance the image in such a way so that, it will be suitable for further processing. It is very important for all imaging applications especially for biomedical domain where, the accuracy is the major concern. That is why pre-processing is necessary for most of the cases in biomedical image analysis. Developing suitable and effective image enhancement techniques are of major interests of many researchers. It also helps physicians to easily interpret an image. Now, the enhancement can be of different types and the choice is dependent on the image as well as on the application. Many methods have been already proposed. In recent years, several methods based on meta-heuristic and soft computing tools have been developed apart from traditional methods. In this paper, a comprehensive review of the application of meta-heuristic and soft computing based tools is provided discusses some of the application of these techniques in biomedical image analysis.