Medical Image Processing - Medical Image Processing: Advanced Fuzzy Set Theoretic Techniques - page 23

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Medical Im age Processing
2.1 Introduction
The environment of medical imaging has changed dramatically by chang-
ing from analogue to digital technology. The widely used techniques are
computed tomography (CT), Doppler imaging, magnetic resonance imaging
(MRI), functional MRI and many others. The main task of image processing
is converting the pictures into digital form. A diversity of problems in image
processing range from image perception to image interpretation. Low-level
image processing is concerned with the pixels, which initially enhances or
filters the image, that is, it preprocesses the image. The next level of the image
processing is concerned with the regions in the image. Here, the features of
different regions or objects are extracted. The next process is high-level pro-
cessing where the whole or parts of the image or series of the images are
considered. The images are segmented for classification and recognition and
finally interpretation. In the high level, the knowledge of experts is involved
for making decisions. The following are the steps that are required in medi-
cal image processing.
2.1.1 Image Contrast Enhancement
The aim of image enhancement is to transform the original image into
another image that is more suitable for further processing. It increases the
contrast of the image by making the dark pixels darker and bright pixels
brighter. As the images, especially the medical images, are not illuminated
properly, many structures are not clearly visible and so contrast enhance-
ment is required, which highlights the structures in the image. So, ini-
tially the images are enhanced and then they are processed, often called
the preprocessing stage. In this stage, the images are filtered to remove
any noise present, which is explained in detail in a different chapter.
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