Development of optimized segmentation map in dual energy computed tomography
2012
Dual energy computed tomography (DECT) has been widely used in clinical practice and has been particularly effective
for tissue diagnosis. In DECT the difference of two attenuation coefficients acquired by two kinds of X-ray energy
enables tissue segmentation. One problem in conventional DECT is that the segmentation deteriorates in some cases,
such as bone removal. This is due to two reasons. Firstly, the segmentation map is optimized without considering the Xray
condition (tube voltage and current). If we consider the tube voltage, it is possible to create an optimized map, but
unfortunately we cannot consider the tube current. Secondly, the X-ray condition is not optimized. The condition can be
set empirically, but this means that the optimized condition is not used correctly. To solve these problems, we have
developed methods for optimizing the map (Method-1) and the condition (Method-2). In Method-1, the map is optimized
to minimize segmentation errors. The distribution of the attenuation coefficient is modeled by considering the tube
current. In Method-2, the optimized condition is decided to minimize segmentation errors depending on tube voltagecurrent
combinations while keeping the total exposure constant. We evaluated the effectiveness of Method-1 by
performing a phantom experiment under the fixed condition and of Method-2 by performing a phantom experiment
under different combinations calculated from the total exposure constant. When Method-1 was followed with Method-2,
the segmentation error was reduced from 37.8 to 13.5 %. These results demonstrate that our developed methods can
achieve highly accurate segmentation while keeping the total exposure constant.
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