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3.4.1 Noise

In digital fluoroscopy the following three sources contribute to digital image noise which limits image quality.

(1 ) Quantum noise (sometimes called quantum mottle because of the mottling effect this noise produces in film images), resulting from detecting a finite number of X-ray photons in each pixel. The greater the number of X-rays used to form an image the smaller is the relative intensity of the noise. For a beam of monoenergetic X-ray photons the relative error in each pixel is proportional to:

4 i (3.6)

yfN

where N is the number of detected X-ray quanta contributing to that pixel. Accordingly quadrupling the number of detected X-rays (and hence patient exposure) will decrease the noise twofold. In a dynamic study with X-ray imaging, the noise cannot be made arbitrarily small because there is a practical limit to the acceptable patient dose and the X-ray flux that can be produced by the X-ray tube in the short period of time required to record a sharp image («0.04 second).

(2) An exposure-independent electronic noise contribution, which originates primarily in the preamplifier stage of the television. This contribution is termed ‘system noise' and enters to a limited degree at all stages of

analogue signal processing.

(3) Digitisation noise, which is due to the discrete increments between grey levels in a digital image, and which can made smaller by increasing the number of grey levels defined by the ADC. Commercially available ADCs provide 1024 grey levels (10 bits) (Shroy 1988).

In general, one of the these three noise sources will dominate a digital fluoroscopy image. In a properly designed and operated image system, the total image noise should be dominated by quantum noise since otherwise the X-ray dose to the patient could be reduced without sacrificing image quality. Low-noise video cameras are used in digital angiography to keep electronic noise well below quantum noise. Quantisation error can be made small compared to overall noise by choosing the grey level assignment to be less than twice the quantum noise (Shroy 1988).

The image subtraction techniques is used to enhance the detectability of low contrast anatomical structures. Subtraction is therefore a method of removing a significant source of noise, patient structure noise due to overlying bone and soft tissue structure. But subtraction does not reduce random noise such as quantum mottle, since this noise changes from one frame to another. Random noise occurs due to the finite number of X-ray photons contributing to the image (quantum noise) and due to random fluctuation in signal in the T.V. pre-amplifier (electronic noise). As this noise is largely un-correlated between successive images the subtracted image will have increased noise. For example, when there is a linear transformation of X-ray intensity to image grey value and the X-ray intensity is approximately the same for mask and opacified images, then the absolute level of the noise will increase by a factor of /2 (Keyes et al 1981). i.e. random noise adds in quadrature.

The most basic measure of image quality is the SNR of the final image. It is defined as the range of intensities to be digitised (the signal) divided by the root- mean-square deviation of intensity (noise). The SNR is frequently expressed using the logarithmic decibel (dB) scale. The signal to noise ratio in dB is equal to 20 log.,o(SNR). Thus, 60 dB correspond to an SNR of 1000:1.

3.4.2 Scatter and Veiling Glare

The X-ray intensity of each pixel in a digital fluoroscopy image is the sum of two components: a primary (direct) component composed of X-rays transmitted straight through the patient; and a secondary (indirect) component composed of X-rays which have been deflected or scattered within the patient before reaching the imaging system. Scattering of light in the output phosphor, or veiling glare, also adds an additional secondary component. With the use of a broad field image intensifier both the primary and scattered X-ray intensity, Sp and Sg, respectively, are detected. This reduces the iodine contrast in a logarithmic difference image by the factor:

(3.7) Sp

compared to the ideal case where only the primary X-ray intensity Sp is detected. Several investigators have tried to estimate and correct scatter and veiling glare (Pfaff et al 1988; Maher et al 1982) but the more practical approach is to calculate an estimated correction from the image by assuming that scatter and veiling glare can be characterised by a point spread function (PSF). Shaw et al (1982) have estimated veiling glare by convolving a fixed PSF with the image and multiplying the result by a weighting factor. Seibert et al (1985) convolved a calibrated inverse filter with the image to remove veiling glare. In our laboratory Arnold and Hawkes (1989) have devised a technique for densitometric calibration using a pair of scanning slits. The technique is designed to remove the effects of X-ray scatter, beam hardening, and veiling glare.

3.5 CONCLUSION

Digital angiography and cine-film angiography employ identical imaging chains from the X-ray tube through to the image intensifier and therefore share the limitations of these systems in terms of resolution, contrast, and noise. The advantages of digital imaging during the angiographic procedure are the speed and ease with which the images can be replayed, the availability of image

enhancement, random access to multiple reference frames from previous views, and increased contrast sensitivity with digital subtraction, allowing a reduction in the volume of injected contrast material. In addition, it is faster to extract quantitative data from digital images than from cine-film.

An important contribution of digital fluorography is the use of subtraction techniques to enhance the detectability of low contrast anatomical structures. Subtraction is therefore a method of removing a significant source of noise, patient structure noise due to overlying bone and soft tissue structure.

The spatial resolution and SNR in digital angiography make this image modality well suited to quantitative studies of the vascular system. The next chapter provides an overview of existing X-ray angiographic techniques of blood flow measurements.

CHAPTER 4

A REVIEW OF QUANTITATIVE X-RAY ANGIOGRAPHIC TECHNIQUES TO