23-01-2013, 02:38 PM
Radiographic Image Processing based Methodology
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Abstract:
For Clinical purposes Medical imaging is the technique and process which is used for creating images of the human body (or parts and function thereof). Although imaging of removed organs and tissues can be performed for medical reasons, such procedures are not usually referred to as medical imaging, but rather are a part of pathology [1]. Basically it is part of biomedical imaging that incorporates radiology, nuclear medicine, endoscopy, investigative radiological sciences, endoscopy, (medical) thermography, medical photography, and Measurement and microscopy[1][2]. Medical imaging is often perceived to designate the set of techniques that noninvasively produce images of the internal aspect of the body. In this restricted sense, medical imaging can be seen as the solution of mathematical inverse problems. This means that cause (the properties of living tissue) is inferred from effect (the observed signal) [1].
Medical Imaging generally uses following technology: Radiography, Magnetic Resource Imaging (MRI), Fiduciary Markers, Nuclear Medicine, Photo Acoustic Imaging, Breast Thermography, Tomography, Ultra Sound, Echocardiography[1].
Introduction
The Image Acquisition Toolbox software is a collection of functions that extend the capability of the MATLAB® numeric computing environment. The toolbox supports a wide range of image acquisition operations, including:
• Acquiring images through many types of image acquisition devices, from professional grade frame grabbers to USB-based webcams
• Viewing a preview of the live video stream
• Triggering acquisitions (includes external hardware triggers)
• Configuring callback functions that execute when certain events occur
• Bringing the image data into the MATLAB workspace
Imaging Features
Synovium and Effusions in normal joints, synovium either cannot be seen, (as with the SE sequences), or can be visualized only as a thin line (3DFT spoiled GRASS). Abnormalities of the synovium are the earliest lesions seen in rheumatoid arthritis (Figure 1).
Application of Image Processing
Processing of digital images include operations involving digital images such as acquisition, storage, retrieval, translation, compression, etc. Conventional examination of the hand radiographs is well established as a diagnostic as well as an outcome measure in Rheumatoid Arthritis (RA). The presence of early soft-tissue swelling is easily recognized on plain radiographs but not readily quantified. Although the presence of early osteoporosis is recognized
in the affected hand, a mild osteoporosis may be extremely subtle to the eyes Use of magnetic resonance (MR) technique has been shown to sensitively detect early local edema and inflammation prior to a positive finding on plain film radiographs. However, MR is an expensive
examination and may not be used as a routine technique. Recent improvements in hardware and software available for digital image processing have led to the quantitative assessment of radiological abnormalities in diagnostic radiology.
Conclusion
In this paper a radiographic Image processing based methodology is presented to accurately and reliably diagnosis of the presence of disease Rheumatoid arthritis. The results presented here are preliminary and focused only the reproducibility aspects of the technique. This technique is being applied towards monitoring early stage rheumatoid arthritis patients in an ongoing clinical trial. Results obtained from the clinical trial data should provide a better understanding. The present article provides thought of better understanding towards the disease in comparative way.