|
KMID : 0357520080310010071
|
|
Journal of Radiological Science and Technology
2008 Volume.31 No. 1 p.71 ~ p.81
|
|
|
Evaluation to Obtain the Image According to the Spatial Domain Filtering of Various Convolution Kernels in the Multi-Detector Row Computed Tomography
|
|
Lee Hoo-Min
Yoo Byung-Gu
Kwon Dae-Chul
|
|
|
Abstract
|
|
|
|
Our objective was to evaluate the image of spatial domain filtering as an alternative to additional image reconstruction using different kernels in MDCT. Derived from thin collimated source images were generated using water phantom and abdomen B10(very smooth), B20(smooth), B30(medium smooth), B40 (medium), B50(medium sharp), B60(sharp), B70(very sharp) and B80(ultra sharp) kernels. MTF and spatial resolution measured with various convolution kernels. Quantitative CT attenuation coefficient and noise measurements provided comparable HU(Hounsfield) units in this respect. CT attenuation coefficient(mean HU) values in the water were values in the water were , air() and noise in the water(), air(). In the abdominal fat a CT attenuation coefficient() and noise() was measured. In the abdominal was CT attenuation coefficient() and noise() in the muscle and in the liver parenchyma of CT attenuation coefficient() and noise () in the liver parenchyma. Image reconstructed with a convolution kernel led to an increase in noise, whereas the results for CT attenuation coefficient were comparable. Image scanned with a high convolution kernel(B80) led to an increase in noise, whereas the results for CT attenuation coefficient were comparable. Image medications of image sharpness and noise eliminate the need for reconstruction using different kernels in the future. Adjusting CT various kernels, which should be adjusted to take into account the kernels of the CT undergoing the examination, may control CT images increase the diagnostic accuracy.
|
|
|
KEYWORD
|
|
|
Kernel, MTF, CT Attenuation Coefficient, Noise, Computed Tomography
|
|
|
FullTexts / Linksout information
|
|
|
|
|
|
Listed journal information
|
|
|
|