Image processing in health informatics

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Abstract

There is no doubt that the image has become the most common source of information in all ways as it carries a huge amount of natural descriptions about the corresponding scene. Recently, biomedical images-based applications have received more attention from the image processing and health informatics research communities. Principally, biomedical image processing has become interesting in its multidisciplinary nature. The medical image processing can be executed in 2D, 3D or even multi-dimensional images to extract useful information. These images serve in the ultimate goals of clinical activities such as monitoring, diagnosis, localization, and treatment. Nowadays, there is an inevitable need to get a concrete surgery system to help and automate the clinical workflow to solve in a shorter period. As well, providing the medical images in high quality and fascinating storage may contribute in such surgery systems. Therefore, in this chapter, we shortly cover core principal medical image processing techniques, image enhancement, and compression. We consider to cover these techniques as they handle the most two challenges in biomedical imaging, which are image quality and image storage/transmission. We focus on three main types of medical images: magnetic resonance imaging (MRI), X-ray/computed tomography (CT), and Ultrasound images. Furthermore, we report the usage of image processing-based techniques in the recent medical imaging systems and technologies.

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Shehata, A., Salem, M., & Ahad, M. A. R. (2021). Image processing in health informatics. In Intelligent Systems Reference Library (Vol. 192, pp. 145–170). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-54932-9_6

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