High Pixel Values Research Articles

Imaging of Ventilation with Dual-Energy CT during Breath Hold after Single Vital-Capacity Inspiration of Stable Xenon

To assess single-breath-hold technique for ventilation mapping by using dual-energy computed tomography (CT) in phantom experiments and volunteers. Institutional review board approved this study, and written informed consent was obtained from all volunteers. A rubber bag filled with a mixture of xenon (0%-35.4%) and oxygen was scanned with dual-source dual-energy CT (80 kV and 140 kV with tin [Sn] filter [Sn/140 kV] and 100 kV and Sn/140 kV). A cylinder containing six tubes of identical sizes with different apertures was ventilated once with a mixture of 35% xenon and 65% oxygen and was scanned in dual-energy mode (80 kV and Sn/140 kV). Xenon-enhanced images were derived by using three-material decomposition technique. Four volunteers were scanned twice in dual-energy mode (80 kV and Sn/140 kV) during breath hold after a single vital-capacity inspiration of air (nonenhanced) and of 35% xenon. Xenon-enhanced images were obtained by using two methods: three-material decomposition and subtraction of nonenhanced from xenon-enhanced images. Regression analysis with t and F tests was applied to the data of the rubber bag scans, with the significance level set at .05. Mean pixel values of gas in the bag were linearly related to xenon concentration for all x-ray tube voltages (r(2) = 1.00, P < .00001). Pixel values of the xenon-enhanced images of the tubes were related to their aperture size. Nearly homogeneous (coefficient of variation: 0.22, 0.23, and 0.34) pixel values were found in the lungs of healthy volunteers, with higher pixel values in the trachea and lower pixel values in the bullae. Xenon-enhanced images calculated by using three-material decomposition had better image quality on visual comparison than those calculated by using subtraction. Xenon-enhanced dual-energy CT with the single-breath-hold technique could depict ventilation in phantoms and in four volunteers.

SU‐E‐T‐283: Deforming Planning CT Images to CBCT Images Using MIMVista

Purpose: The overarching goal of this project is to be able to use daily CBCT images to calculate the dose delivery for a single treatment. To calculate the dose, planning CT images can be deformed to match the patient anatomy at the time of delivery as shown in the daily CBCT. Our current research is looking into methods to deform the planning CT to best match the CBCT using the commercial software MIMVista. Methods: The OBI (on‐board imager) of a Varian Linac at Karmanos Cancer Institute was used to get a set of daily CBCT images for a prostate patient. The images were processed in MatLab on a voxel‐by‐voxel basis to enhance areas of low signal and to convert HU for the CBCT to HU for the planning CT. Efforts were also made to decrease signal saturation in the bone through high pixel value masking. The planning CT images were deformed to the new CBCT images using MIMVista software. Results: Converting the HUs from CBCT to planning CT values followed by applying different scaling factors gave some success in improving the deformation of the images using MIMVista. However, the resulting deformation is clearly not yet accurate enough to be applied clinically. Deformation was performed by aligning bony anatomy, therefore bony anatomy deformed significantly better than tissue. Regions of low signal, variable bladder filling, and bowel gas pockets present difficulties that still need to be resolved. Conclusions: While the CBCT image adjustments we have made have improved MIMVistaˈs ability to deform planning CT images to CBCT images, work still needs to be done to reduce the noise in the CBCT images so that the planning CT images will be able to be deformed accurately.

An Novel Chaotic Image Encryption Algorithm based on Tangent-Delay Ellipse Reflecting Cavity Map System

In order to effectively protect digital image information, to improve the efficiency and security of the encrypted image, many effective and feasible image encryption algorithms have been proposed. The recovery is depended on the recovery value of pixel 8 bits plane; the incorrect from low to high pixel value of plane affect the incorrect of Index of all proportion to the pixel value, resulting in the restoration of image quality. Based on the study of digital image encryption technology, the essay proposes the image encryption algorithm based on TD-RECS chaotic system, and the decryption algorithm against attack on the basis of it.

Two-dimensional Simulation of Aerosol?Cloud Profile

Developments of algorithm and computer graphics simulation are important to distinguish between aerosols and clouds in remote sensing data and images. The distribution of aerosols and clouds are needed to be known in order to study their interactions with one another and identify both affecting factors towards Earth’s climate stability. The objective of this paper is to expand the current work done in building new algorithm and simulation method to differentiate aerosols and clouds in spaceborne lidar data and images using image processing and computer graphics software, PCI Geomatica 10.1 and SCION Image. The new algorithm and simulation that has developed showed good results and clarify the vertical distribution of aerosols and clouds in the atmosphere. Plot profiles of clouds on both days showed higher pixel values than aerosol which are 255 compared to 234.04 and 244.11 for aerosols. Aerosols have been found consistently to have higher mean at altitude 0?5 km and 15?20 km on both days.

Principal component analysis with optimum order sample correlation coefficient for image enhancement

Principal component analysis (PCA) has been commonly used and has played an important role in remote sensing for information extraction. However, the ordinary PCA based on second‐order covariance or correlation is capable of forming components on the basis of the statistical properties of a majority of pixel values – pixel values around mean values. For many applications, principal components should be constructed on the basis of optimum correlation coefficients so that the components can represent low or high values of minority pixels of interest. A new version of the PCA has been proposed on the basis of an optimum order sample correlation coefficient for enhancing the contribution of the image bands including the low or high minority pixel values that can assist in extracting weak information for image classification and pattern recognition. The ordinary PCA becomes the special case of the new version of the PCA introduced in this paper. The new method was validated with a case study of identification of Au/Cu‐associated alteration zones from a Landsat Thematic Mapper (TM) image in the Mitchell‐Sulphurets district, Canada.

TH-C-T-6E-05: Evaluation of GafChromic EBT Film for IMRT QA Using Two Different Scanners

Purpose: Absolute film dosimetry for IMRT QA using radiographic film is very time‐ and film‐consuming because of film processing uncertainties. Radiochromic film requires only one calibration curve per energy per production lot. Applicability of new GafChromic EBT film for absolute IMRTdosimetry using two different film scanners was evaluated. Method and Materials: GafChromic EBT (ISP, Wayne, NJ) and Kodak EDR2 films irradiated in polystyrene phantoms on a Varian 2100C/D linear accelerator were compared using the Vidar VXR‐16 DosimetryPro and Epson Expression 1680 scanners. Vidar scanning was done with RIT113 software and a yellow filter for the EBT. Epson scans were done with the scanner software in 48 bit color, followed by red channel extraction. EBT films were scanned 24 hours after exposure. MSKCC's Contour software was used for dosimetric analysis. Results: EBT provided better intensity linearity with dose than EDR2 and higher pixel values in the clinical dose range. The pixel values of the EBT film differed by 3–9% (Epson) and 11–19% (Vidar) when rotating the film 90 degrees on the scanner, which resulted in up to 30% dose errors when mixing directions of IMRT and calibration films. The Vidar produced lower pixel values but higher optical density than the Epson. Calibration curves based on small films cut from one sheet coincided with the curves created from a set of sheets. EBT film IMRT dose distributions agreed well with EDR2 (1.9% on CAX for the Vidar, 3.6% for the Epson). Conclusion: GafChromic EBT film provides a good alternative for absolute IMRTdosimetry. Both film scanners provide equivalent dosimetric results. Calibration films and IMRT films have to be scanned in the same direction. The calibration curve can be created using small films cut from one large film. Conflict of Interest: Partial material support provided by ISP Corporation.

Initiation of convective cells in relation to water vapour boundaries in satellite images

Strong convection and severe thunderstorms can be observed within specific synoptic situations: on the one hand associated with fronts or frontal zones, on the other hand under “fair-weather” conditions. Comprehensive observations of satellite images and sequences show that the first appearance of deep convection under “fair-weather” conditions can be associated to the transition zone between relatively high pixel values and relatively low pixel values in the WV satellite imagery. This boundary represents not only the transition between relatively humid and dry air at levels above 600 hPa but also has typical characteristics in other parameters and/or processes which favour the growth of convective cells. The fact of the first appearance of deep moist convection at brightness boundaries in the WV imagery can be used for regional Nowcasting.

Accuracy of stereotactic coordinate transformation using a localisation frame and computed tomographic imaging. Part I. Influence of the mathematical and physical properties of the CT on the image of the rods of the localisation frame and the determination of their centres.

The accuracy of coordinate transformation from the computed tomographic (CT) space to the stereotactic frame space was analysed for frame-based stereotactic systems which use a localisation frame and coordinate transformation based on matrix calculation. The coordinate transformation was divided into three consecutive steps: (1) transforming the localisation frame into the CT image built up from pixels with distinct attenuation values, (2) determining the rod centres of the localisation frame in the CT image, and (3) coordinate transformation from the image to the frame space using the centres of the rods in the image space and algebraic, matrix-based calculation. The error contribution at each step was evaluated separately and its effect on the subsequent mathematical operations was analysed. The first step dealt with the influences of the mathematical and physical properties of the CT on the image of the localisation frame. Noise, slice thickness, convolution filter, dimension of the pixel matrix, and image processing had an influence on the attenuation values in each pixel. Above all, the slice thickness had an effect on the shape of the oblique rods in the CT image. At the second step, the main error contribution was due to the method by which the centre of the rods was calculated. The most accurate method was to determine the centre of gravity using the attenuation values as single mass points (with accuracy in the range of +/-1/10 pixel, or +/-0.125 mm), followed by rounding off the centre of gravity and the highest pixel value in the square matrix R2(N) within 1 pixel. Pointing with a cursor under visual control was accurate to 1 pixel and the pixel with the highest attenuation value showed deviations of up to 2 pixels in the x and y axes. Thus, the methods differed by a factor of 20. The influence of the CT mathematics and physics on the determination of the centre of the fiducials was negligible in comparison to the method of calculation used. There was no systemic error due to the filtred back projection algorithm. Data input errors due to noise were in the range of 1/10 pixel. The effects of the remaining physical influences were all in the range of the error due to noise. In particular these results speak in favour of no influence of slice thickness on coordinate transformation.

Primary breast abnormalities: selective pixel sampling on dynamic gadolinium-enhanced MR images.

To evaluate a region-of-interest (ROI) analytic method that involves selective sampling of pixels within predetermined ranges of contrast material enhancement values ("thresholding") on magnetic resonance (MR) images of primary breast abnormalities. Dynamic gadolinium-enhanced MR images were obtained in 105 women. ROIs were drawn to outline the full extent of lesions. Relative signal intensity increase was determined on a pixel-by-pixel basis on 1- and 2-minute postcontrast images, as was the maximum relative signal intensity increase. Thresholding was used to analyze each ROI, with the upper boundary defined by the highest pixel value and lower boundaries of 0%-100%. Seventy-one invasive carcinomas and 37 benign lesions were analyzed. Narrower thresholding (i.e., larger percentage) resulted in an increase in all enhancement ratios (P < .0005). The enhancement ratio on 1-minute postcontrast images differed between benign lesions and carcinomas (P < .0005), but there were no significant differences in 2-minute and maximum ratios. Mean enhancement differences between benign and malignant lesions increased with narrower thresholding, but variability also increased linearly. Results of receiver operating characteristic analysis showed that thresholding did not affect the diagnostic usefulness of enhancement ratios. Contrary to current opinion, selective sampling of the most enhancing areas of breast abnormalities may not provide any diagnostic advantage over the use of easily drawn, lesion-encompassing ROIs.

Inherent bias in correlation averaged images.

The correlation averaging algorithm frequently used to enhance micrographs of repeating structures contains an inherent bias that favours images with larger pixel values or positive noise levels. This bias not only skews the composite image toward higher pixel values, but also distorts the image by increasing the value of high-valued pixels more than that of low-valued pixels. These errors are especially important in scanning probe microscopy images where the pixel value reflects a distinct height. A similar algorithm that uses a structure function in place of the correlation function eliminates this bias.