Bio-medical image enhancement using hybrid metaheuristic coupled soft computing tools

Shouvik Chakraborty, Kalyani Mali, Sankhadeep Chatterjee, Soumen Banerjee, Aayush Sah, S. Pathak, Suparba Nath, Debkumar Roy
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引用次数: 14

Abstract

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.
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混合元启发式耦合软计算工具的生物医学图像增强
生物医学图像分析方法被认为是筛查、检测和诊断的有效而重要的工具。它几乎是不可避免的工具,并作为医生的援助之手。与生物医学图像相关的主要问题之一是,大多数图像(不同模态)都受到噪声和其他不同质量相关问题的影响,如对比度差、模糊和难以提取合适的信息。因此,有必要设计一些技术来增强图像,使其适合于进一步的处理。它对所有成像应用都非常重要,特别是在生物医学领域,精度是主要关注的问题。这就是为什么在生物医学图像分析的大多数情况下,预处理是必要的。开发合适而有效的图像增强技术是许多研究者的主要兴趣。它还能帮助医生更容易地解读图像。现在,增强可以有不同的类型,选择取决于图像和应用程序。人们已经提出了许多方法。近年来,在传统方法的基础上,发展了基于元启发式和软计算工具的几种方法。在本文中,综合回顾了基于元启发式和软计算的工具的应用,讨论了这些技术在生物医学图像分析中的一些应用。
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