The detection of very subtle lesions and/or lesions overlapped with vessels on CT images is a time consuming and
difficult task for radiologists. In this study, we have developed a 3D temporal subtraction method to enhance interval
changes between previous and current multislice CT images based on a nonlinear image warping technique. Our
method provides a subtraction CT image which is obtained by subtraction of a previous CT image from a current CT
image. Reduction of misregistration artifacts is important in the temporal subtraction method. Therefore, our
computerized method includes global and local image matching techniques for accurate registration of current and
previous CT images. For global image matching, we selected the corresponding previous section image for each
current section image by using 2D cross-correlation between a blurred low-resolution current CT image and a blurred
previous CT image. For local image matching, we applied the 3D template matching technique with translation and
rotation of volumes of interests (VOIs) which were selected in the current and the previous CT images. The local shift
vector for each VOI pair was determined when the cross-correlation value became the maximum in the 3D template
matching. The local shift vectors at all voxels were determined by interpolation of shift vectors of VOIs, and then the
previous CT image was nonlinearly warped according to the shift vector for each voxel. Finally, the warped previous
CT image was subtracted from the current CT image. The 3D temporal subtraction method was applied to 19 clinical
cases. The normal background structures such as vessels, ribs, and heart were removed without large misregistration
artifacts. Thus, interval changes due to lung diseases were clearly enhanced as white shadows on subtraction CT
images.
The purpose of this study is to investigate the influence of the scattered x rays on the signal sharpness on the radiographs produced by using a computed radiography (CR) system by measuring the spatial frequency spectra of the signal image. By using a 0.1 mm slit on the polymethyl methacrylate (PMMA) for thicknesses of 0.5 cm to 20.5 cm, the slit images were acquired as a signal by use of imaging plates at tube voltages of 50 kV to 120 kV. The relative exposure profiles for the slit images were Fourier transformed to obtain the spatial frequency spectra. For comparison of the frequency spectra with and without the scattered x rays, we defined the scattered x-ray influence factor (SIF) representing the magnitude of the influence of the scattered x rays on the spatial frequency spectra of the signal image. To investigate the contribution of the primary and scatter components to the degradation of the signal sharpness, we proposed a method for separating the spatial frequency spectrum of the signal image into the primary and scatter components. By obtaining the SIF, we found that, for very lower frequencies (less than about 0.3 mm^-1), the shape of the spatial frequency spectra of the signal image depends on the scattered x rays, but, for higher frequencies, hardly depends. As a result of the separation of the frequency spectra of the signal image, we found that the contribution of the scatter component for very lower frequencies (less than about 0.2 mm^-1) to the total spectrum of the signal image was not negligible and became greater as the scattering material thickness and the tube voltage increased. On the contrary, for higher frequencies, the primary component was dominant compared with the scatter component for all thicknesses and tube voltages.
The presampling modulation transfer function (MTF) can be determined by the edge spread function in which the sampling interval is narrower than the pixel-to-pixel interval from slight angled edge image. It is important that the precision of the presampling MTF depend on the precision of the edge angle. In this study, we have developed the automated method, which includes a precise edge angle determination process for the measurement of the presampling MTF.
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