Image Processing
in Computed Radiography
Pieter Vuylsteke, Ph.D.
Emile Schoeters, Ph.D.
Agfa-Gevaert N.V.
International Symposium on
Computerized Tomography for Industrial Applications
and Image Processing in Radiology
Berlin, Germany
March 15-17, 1999
R&D Equipment
2
1. ABSTRACT 3
2. INTRODUCTION 3
3. CR IMAGE PROCESSING OVERVIEW 3
4. IMAGE CONTRAST ENHANCEMENT 5
4.A. Edge enhancement 5
4.B. Dynamic range compression 7
4.C. Multiscale contrast enhancement 7
4.C.1. The multiscale representation 8
4.C.2. Contrast equalization 10
4.C.3. Frequency processing 12
5. CONCLUSION 15
6. ACKNOWLEDGMENTS 15
7. REFERENCES 15
3
1. ABSTRACT
This article starts with an overview of image processing techniques used in storage phosphor
based Computed Radiography (CR) systems. Next it elaborates on a selection of image enhancement
algorithms. Both the working principles and image quality issues are discussed. The main focus is on
multiscale image enhancement, which has become state-of-the-art.
2. INTRODUCTION
Since the early days of CR technology developers have investigated solutions for bridging the
gap between the very large dynamic range that characterizes the CR detector and the limited range of
the output medium and viewing process. A considerable part of image processing functionality in
current CR systems deals directly or indirectly with the issue of manipulating image contrast, in such
a way that all relevant image features are rendered to an appropriate level of visibility, despite the
restriction of viewing density range. CR equipment manufacturers have adopted basic image
processing techniques, or they have developed dedicated solutions.
With this article it is our aim to provide a better understanding of the essential image
enhancement techniques of CR systems, what their purpose is, how they operate, and how they affect
image quality.
3. CR IMAGE PROCESSING OVERVIEW
A simplified diagram of the image processing operations in current CR systems is depicted in
Fig. 3.1. The ensemble of operations applied to the stream of image data could be roughly entitled
‘image enhancement’. The role of image processing functions within this data path is to improve the
visual quality of the CR image in terms of spatial resolution, sharpness, contrast resolution, dynamic
range, SNR. The processing efforts in the main path have to do with maximizing the information
transfer to the viewer. The enhancement of image contrast is the main topic of this article and will be
elaborated in section 4.
The image processing operations are controlled by parameters, which often are assigned a
value in accordance with the examination type. The predefined parameter values are stored in tables,
with entries for each examination type. Specification of the examination type is done immediately
before or after each exposure by means of an identification terminal, and hence is prone to human
errors.
In current CR systems some image processing functions are controlled by internal parameters
which are derived from the actual image data. The parameter values are estimated by heuristic
algorithms. This way the kind and degree of enhancement are adapted to the specific characteristics of
the image in terms of density levels, dynamic range, noise level, or the presence of irrelevant regions
like collimation borders. In most cases a reduced version of the original image is used as input for
analysis, since this still contains the essential data for the task at hand. Although the final purpose of
the analysis work is very similar among different equipment, most algorithms are proprietary, so that
only little is published about their actual implementation. |
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