Fig. 4.1
An example of radiography use during barium enema to evaluate the mucosa and microscopic folds of the stomach
Fig. 4.2
An example of radiography use during postoperative treatment to observe the entire abdomen and to confirm the position of a catheter tip
4.1.1 Dynamic Range Compression
Chest radiographs should be displayed on a large dynamic range because the thorax is composed of a large variety of anatomical tissues. Dynamic range compression (DRC) is a technique that can successfully preserve a detailed high contrast and reduce the dynamic range viewing systems. This technique makes it possible to change black-mashed areas to areas that are visible enough for adequate diagnosis (Fig. 4.3). Blurred images from the high-frequency component are removed from the original images to render the final contour-enhanced images. This final image shows an improved “black-mashed” image while maintaining the contour-enhanced area.
Fig. 4.3
DRC depicts small vessels in the right lower lobe. This technique improves visibility of dense peripheral tissues by applying varying degrees of contrast within an identical image. (a) DRC on and (b) DRC off. DRC, dynamic range compression
4.1.2 Spatial Frequency Filtering
Frequency filters process an image in the frequency domain based on the Fourier transform. The operator usually takes an image and a filter function in the Fourier domain. This image is then multiplied pixel by pixel with the filter function. Thereafter, the image is retransformed into the spatial domain, where attenuating high frequencies result in a smoother image, whereas attenuating low frequencies enhance the edges. This technique of applying spatial frequency to structures of different sizes within the same image improves visibility. Multifrequency processing, which combines traditional DRC and flat panel (FP), is also available (Fig. 4.4).
Fig. 4.4
This set of images illustrates the effective use of spatial frequency filter in providing better depiction of the mediastinum while maintaining the contrast of the lungs. (a) Without spatial frequency filter and (b) with spatial frequency filter
4.1.3 Recursive Filter
This filter calculates output values based on the latest input. Execution of this filter is very easy, but it lacks flexibility and sometimes results in recognizing a subject’s motion as persistence of image (Fig. 4.5).
Fig. 4.5
This is an example on how recursive filter works by reducing noise on a clinical chest image. However, the end of the guide sheath is blurred out. (a) Without recursive filter and (b) with recursive filter
4.2 Tomosynthesis
4.2.1 A New Tomography Method
In conventional x-ray, the regions of interest (ROI) are sometimes difficult to set because of cluttering of signals from above and below. Conventional tomography has been previously used, especially in orthopedics, to produce one image per x-ray projection, which is time-consuming. Furthermore, image flow is sometimes produced and leads to low diagnostic quality.
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