Abstract
When medical images are processed by morphological operations, they provide substantial amount of utilizable information. The technological advancement in the field of image analysis and medical imaging domain acquiesces the understating of detection and diagnosis of disease to enhance the quality of medical treatment. Application of image processing in medical imaging field administers the development of processing nebulous, skeptical, reciprocal, superfluous information, and data for a vigorous structural attribute. To understand any image, the human and artificial astuteness system matches the features extracted from an image. Image enhancement is a decisive stage in image processing system. It intents at convalescencing the ocular data and the informational trait of wry images. After the acquisition of an image, if it is of poor quality, it requires enhancement. Various available techniques can be applied for enhancement; some are providing good results with limitation of computing time. A new intelligent algorithmic approach, based upon biologically inspired approaches, is suggested for image enhancement. In this ambience, this article describes about one of the most commonly used algorithms known as artificial bee colony algorithm, and its various types, used for image enhancement in different subdomains of medical imaging, are covered here.
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Ahmad, R., Choubey, N.S. (2018). Review on Image Enhancement Techniques Using Biologically Inspired Artificial Bee Colony Algorithms and Its Variants. In: Hemanth, J., Balas , V. (eds) Biologically Rationalized Computing Techniques For Image Processing Applications. Lecture Notes in Computational Vision and Biomechanics, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-61316-1_11
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