Abstract

Abstract This article deals with several image postprocessing concepts that are now commonplace in digital imaging in medicine. First, the motivation for the development of digital imaging modalities is described, followed by a rationale for understanding image postprocessing operations that have become common in radiology. Second, the image domain concept is outlined with a focus on the characteristics of a spatial location domain image including the matrix, pixels, and the bit depth. In addition, the transformation of the spatial location domain image into the spatial frequency domain is described. The third topic addresses five classes of image processing algorithms including image restoration, image analysis, image synthesis, image enhancement, and image compression. The article continues with a detailed description of point processing operations as well as local processing operations. The former is discussed in terms of the histogram, look-up table (LUT), and windowing. The latter describes spatial location filtering (convolution) and spatial frequency filtering using high- and low-pass digital filters, followed by a brief description of the unsharp masking technique. The fifth major topic presents essential features of the commercially available image postprocessing tool Photoshop, with applications in medical imaging and an emphasis on how this tool can be used by teachers and students alike in an educational environment. Finally, a technical overview of image compression is reviewed with a discussion of compression ratio and types of image compression techniques. In particular, irreversible compression is outlined briefly, and its effect on the visual quality of images is demonstrated. Furthermore, a statement from the Canadian Association of Radiologists (CAR) on the use of irreversible compression in digital radiology is provided. The article concludes with a summary of image postprocessing as an essential tool for those who work in a digital imaging environment.

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