In this paper, we propose an algorithm for reliable segmentation of the lung at HRCT of DILD. Our method consists of
four main steps. First, the airway and colon are segmented and excluded by thresholding(-974 HU) and connected
component analysis. Second, initial lung is identified by thresholding(-474 HU). Third, shape propagation outward the
lung is performed on the initial lung. Actual lung boundaries exist inside the propagated boundaries. Finally, subsequent
shape modeling level-set inward the lung from the propagated boundary can identify the lung boundary when the
curvature term was highly weighted. To assess the accuracy of the proposed algorithm, the segmentation results of 54
patients are compared with those of manual segmentation done by an expert radiologist. The value of 1 minus volumetric
overlap is less than 5% error. Accurate result of our method would be useful in determining the lung parenchyma at
HRCT, which is the essential step for the automatic classification and quantification of diffuse interstitial lung disease.
Automatic liver segmentation is still a challenging task due to the ambiguity of liver boundary and the complex context
of nearby organs. In this paper, we propose a faster and more accurate way of liver segmentation in CT images with an
enhanced level set method. The speed image for level-set propagation is smoothly generated by increasing number of
iterations in anisotropic diffusion filtering. This prevents the level-set propagation from stopping in front of local
minima, which prevails in liver CT images due to irregular intensity distributions of the interior liver region. The
curvature term of shape modeling level-set method captures well the shape variations of the liver along the slice. Finally,
rolling ball algorithm is applied for including enhanced vessels near the liver boundary. Our approach are tested and
compared to manual segmentation results of eight CT scans with 5mm slice distance using the average distance and
volume error. The average distance error between corresponding liver boundaries is 1.58 mm and the average volume
error is 2.2%. The average processing time for the segmentation of each slice is 5.2 seconds, which is much faster than
the conventional ones. Accurate and fast result of our method will expedite the next stage of liver volume quantification
for liver transplantations.
We propose a robust surface registration using a Gaussian-weighted distance map (GWDM) for PET-CT brain fusion. Our method is composed of four steps. First, we segment the background of PET and CT brain images using 3D seeded region growing and apply inverse operation to the segmented images for getting head without holes. The non-head regions segmented with the head are then removed using the region growing-based labeling and the sharpening filter is applied to the segmented head in order to extract the feature points of the head from PET and CT images, respectively. Second, a GWDM is generated from feature points of CT images to lead the feature points extracted from PET images with large blurry and noisy conditions to robustly align at optimal location onto CT images. Third, similarity measure is evaluated repeatedly by weighted cross-correlation (WCC). In our experiments, we evaluate our method using software phantom and clinical datasets with the aspect of visual inspection, accuracy, robustness, and computational time. In our method, RMSE for translations and rotations are less than 0.1mm and 0.2o, respectively in software phantom dataset and give better accuracy than the conventional ones. In addition, our method gives a robust registration at optimal location regardless of increasing noise level.
To detect cerebral aneurysms, arterial stenosis, and other vascular anomalies in a brain CT angiography, we propose a novel technique of cerebral vessel visualization by patient motion correction. Our method has the following steps. First, a set of feature points within the skull base is selected using a 3D edge detection technique. Second, a locally weighted 3D distance map is constructed for leading our similarity measure to robust convergence on the maximum value. Third, the similarity measure between feature points is evaluated repeatedly by selective cross-correlation (SCC). Fourth, the 3D bone-vessel masking and subtraction is performed for completely removing bones. Our method has been successfully applied to five different patients datasets with intracranial aneurysms obtained from 16-slice multi-detector row CT scanner. The total processing time of each datasets was less than 20 seconds. The performance of our method was evaluated with the aspects of accuracy and robustness. For accuracy assessment, we showed results of visual inspection in two-dimensional and three-dimensional comparison of a conventional method and the proposed method. While the quality of the conventional method was substantially reduced by patient motion artifacts, our method could keep the quality of the original image. In particular, intracranial aneurysms were well visualized by our method. Experimental results show that our method is clinically promising by the fact that it is very little influenced by image degradation occurred in bone-vessel interface. For all experimental datasets, we can clearly see intracranial aneurysms as well as arteries on the volumetric images.
In this paper, we present a novel technique of improving vessel visualization quality by removing motion artifacts in
digital subtraction brain CT angiography. The proposed methods based on the three key ideas as follows. First, the
method involves the automatic selection of a set of feature points by using a 3D edge detection technique based on
image gradient of mask and contrast volume. Second, locally weighted-3D distance map is generated to derive to robust
convergence on the optimum value. Third, the similarity measure between extracted feature points is evaluated
repeatedly by selective cross-correlation. The proposed method has been successfully applied to pre- and post-contrast
CT angiography based on brain dataset for global and spatial motion correction. The feature point selection, introducing
local processing on areas of interest consisting of voxels belonging to object boundary only, are very fast compared to
all traditional algorithms where entire volume are searched. Since the registration estimates similarity measures between
feature points and derive to robust convergence on the optimum value by the locally weighted-3D distance map, it offers
an accelerated technique to accurately visualize vessels of the brain.
A simple, easy-to-use and reliable method called nano-bending method is proposed to measure the residual stresses of surface-micromachined structures for MEMS (Micro-Electro-Mechanical Systems). The basic concept is based on the fact that the linear bending stiffness of the surface-micromachined bridge is affected by the residual stress of the consisting materials. It is preferentially necessary to know anchor stiffness and bending stiffness of the surface-micromachined cantilevers in the stress free state which are composed of the same materials as the surface-micromachined bridges. The usefulness of the method was demonstrated by poly-silicon surface-micromachined structures under various residual stresses. The results indicated that the measured residual stress of the as-deposited poly-silicon film is 142.70 MPa with standard deviation of 3.5 percent and the compressive residual stress decreases as growing the annealing effect.
In this paper, we proposed the digital watermarking for a color image. In order to embed watermark signal, we consider the characteristics of HVS (human visual system) and focus on the relatively insensitive components of a color image. In YCrCb color space, Y component is achromatic--luminance and both Cr and Cb components are chromatic--color. At the Cr-Cb chrominance plane, an angle of a pixel represents the hue component of a color that refers to its average spectral wavelength and differentiates different colors and a magnitude of a pixel determines the amount of purity of the color. Because the variation of saturation is less sensitive than that of hue, we modify the saturation value--the magnitude in Cr-Cb chrominance plane. On changing the chrominance data, the phase of a point has to be fixed and only the magnitude of the point that represents the saturation is changed based on the acceptable degree of color difference. The proposed digital watermarking method has a good property in the field of invisibility.
Color histogram is widely used in image retrieval due to its simplicity and fast operation sped. Since color histogram describes only global color distribution in an image, it is not robust to large changes in appearance and shape caused by viewing position, camera zoom, etc. To overcome this problem, we propose the method using the color edge information. Although changes in appearance and shape happen, the pair of colors on the color edge does not change. So we use the global distribution of pairs of colors on the color edge pixel to cope with large appearance change. In the proposed method, color edge detection based on vector angle is performed to classify the pixels of image into smooth and edge pixels. For edge pixel, the global distribution of pairs of colors around the edge is represented by 36 non-uniform colors. In the smooth compressed by DCT. Joint histogram of compressed the 2D chromaticity histogram and the global distribution of pairs of colors is very robust to large appearance changes.
Photoluminescence (PL) measurements on as-grown and hydrogenated In-doped CdTe epitaxial films grown on p-CdTe (211) substrates by molecular beam epitaxy have been performed in order to investigate the optical properties and the hydrogenation effects of In-doped CdTe films. The temperature dependence of the PL intensities for the as-grown In-doped CdTe films show that the peak at 1.590 eV observed at 12 K is related to shallow donor band recombination (D, h). Inhomogeneous broadening of the full width at half maximum for the (D, h) peak might be related to the change from correlated electron and hole distributions in the low-temperature region below 20 K to random electron and hole distribution in the relatively high-temperature region above 40 K. The PL spectrum for the hydrogenated In-doped CdTe films shows that the intensity of the (D, h) peak decreases dramatically and that their longitudinal optical phonons disappear. These results indicate that the PL intensity and the linewidth of the (D, h) peak in as-grown In-doped CdTe films are strongly related to the distribution behavior of the electrons and the holes and that the decrease of the PL intensity of the (D, h) peak for the hydrogenated In-doped CdTe epilayer originates from the passivation effect of the ionized In donor level due to the hydrogenation.
We obtained the photoluminescence spectra for CdTe(111) grown on Si(100) tilted toward <011> 1 degree, 2 degrees, 4 degrees and 8 degrees by MBE before and after RTA. It is caused by the strain due to the lattice mismatch between CdTe epitaxial layer and the substrate that the shift of peaks form CdTe(111)/Si(100) epitaxial layer was observed comparing with that of bulk. We could guess the crystal structures of the CdTe(111) epitaxial layers from the strains calculated from the quantity of the shifts. We found that the crystal structure of CdTe changed from the cubic in bulk to the tetragonal in strained as-grown samples, and from the tetragonal to the trigonal after RTA. It is caused by the different strain type that the structures are different before and after RTA because the misfit for atomic distance is dependent on the direction between CdTe(111) and Si(100). We found that the inplain compressive strains change from asymmetry to symmetry about (111) direction in CdTe(111) epitaxial layer after RTA.
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