Biomedical Image Enhancement Using Different Techniques - A Comparative Study
In medical applications, processing of various medical images like chest X-rays, projection images of trans-axial tomography, cineangiograms and other medical images that occur in radiology, ultrasonic scanning and nuclear magnetic resonance (NMR) is requ
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Abstract. In medical applications, processing of various medical images like chest X-rays, projection images of trans-axial tomography, cineangiograms and other medical images that occur in radiology, ultrasonic scanning and nuclear magnetic resonance (NMR) is required. These images may be used for patients’ screening and monitoring for detection of diseases in patients. Image enhancement algorithms are employed to emphasize, smoothen or sharpen image features for display and analysis. In the biomedical field, image enhancement faces the greatest difficulty in quantifying the criterion for enhancement. Enhancement methods are application specific and often developed empirically. The theme work presented in this paper is a detailed analysis of enhancement of medical images using contrast manipulation, noise reduction, edge sharpening, gray level slicing, edge crispening, magnification, interpolation, and pseudo-coloring. Comparison of these techniques is necessary for deciding an apt algorithm applicable for enhancement of all medical images and further processing. This paper reviews the background of enhancement techniques in three domains i.e. spatial, frequency and fuzzy domain. The comparative analysis of different techniques is shown using results that are obtained by applying these techniques to medical images. Keywords: Biomedical images Image enhancement Fuzzy and spatial domain techniques
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1 Introduction Biomedical image processing is a very broad field. It includes collecting biomedical signals, forming images, processing pictures and displaying images to medical diagnosis on the basis of feature extracted from the image. The existence of image acquisition artifacts, fuzziness, and non-homogeneity of luminance and contrast levels, form, and size of images determines the specificity of biomedical images [1]. In last few years, biomedical image processing has experienced dramatic expansion owing to use of computational resources, magnetic resonance imaging (MRI), Doppler ultrasound, computed tomography (CT), X-ray, optical imaging technologies and nuclear emission based techniques- PET (positron emission tomography), SPECT (single photon emission computed tomography) in medical field. Biomedical imaging focuses on the acquisition of images for both therapeutic and diagnostic purposes. Digital imaging gave rise to CT scanner and allows doctors to © Springer Nature Singapore Pte Ltd. 2018 B. Panda et al. (Eds.): REDSET 2017, CCIS 799, pp. 260–286, 2018. https://doi.org/10.1007/978-981-10-8527-7_22
Biomedical Image Enhancement Using Different Techniques
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watch real-time X-rays on a monitor-a technique called as X-ray fluoroscopy. It helps in guiding invasive procedures such as biopsies and angiograms. A catheter is put into a vein or an artery in the groin to produce images (known as angiograms of blood vessels) in angiography. It is threaded into the blood vessel and is guided to the area to be studied by injecting an X-ray contrast medium through the catheter. This increases the contrast of blo
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