In current HEVC, prediction pixels are finally calculated by linear-function interpolation on two reference pixels. It is hard to expect good performance on the case of occurring large difference between two reference pixels. This paper decides more accurate prediction pixel values than current HEVC using linear function. While existing prediction process only uses two reference pixels, proposed method uses DCT-IF. DCT-IF analyses frequency characteristics of more than two reference pixels in frequency domain. And proposed method calculates prediction value adaptively by using linear-function, DCT-IF and cubic-function to decide more accurate interpolation value than to only use linear function. Cubic-function has a steep slope than linear-function. So, using cubic-function is utilized on edge in prediction unit. The complexity of encoder and decoder in HM6.0 has increased 3% and 1%, respectively. BD-rate has decreased 0.4% in luma signal Y, 0.3% in chroma signal U and 0.3% in chroma signal V in average. Through this experiment, proposed adaptive intra prediction method using DCT-IF and cubic-function shows increased performance than HM6.0.
A robust algorithm to disclose and display the difference of ictal and interictal perfusion may facilitate the detection of ictal hyperfusion foci. Diagnostic performance of localizing epileptogenic zones with subtracted SPECT images was compared with the visual diagnosis using ictal and interictal SPECT, MR, or PET. Ietal and interictal Tc-99m-HMPAO cerebral perfusion SPECT images of 48 patients(pts) were processed to get parametric subtracted images. Epileptogenic foci of all pts were diagnosed by seizure free state after resection of epileptogenic zones. In subtraction SPECT, we used normalized difference ratio of pixel counts(ictal-interictal)/interictal ${\times}100%$) after correcting coordinates of ictal and interictal SPECT in semi-automatized 3-dimensional fashion. We found epileptogenic zones in subtraction SPECT and compared the performance with visual diagnosis of ictal and interictal SPECT, MR and PET using post-surgical diagnosis as gold standard. The concordance of subtraction SPECT and ictal-interictal SPECT was moderately good(kappa=0.49). The sensitivity of ictal-interictal SPECT was 73% and that of subtraction SPECT 58%. Positive predictive value of ictal-interictal SPECT was 76% and that of subtraction SPECT was 64%. There was no statistical difference between sensitivity or positive predictive values of subtraction SPECT and ictal-interictal SPECT, MR or PET. Such was also the case when we divided patients into temporal lobe epilepsy and neocortical epilepsy. We conclude that subtraction SPECT we produced had equivalent diagnostic performance compared with ictal-interictal SPECT in localizing epileptogenic zones. Additional value of these subtraction SPECT in clinical interpretation of ictal and interictal SPECT should be further evaluated.
In vision measurement systems based on structured light, the key point of detection precision is to determine accurately the central position of the projected laser line in the image. The purpose of this research is to extract laser line centers based on a decision function generated to distinguish the real centers from candidate points with a high recognition rate. First, preprocessing of an image adopting a difference image method is conducted to realize image segmentation of the laser line. Second, the feature points in an integral pixel level are selected as the initiating light line centers by the eigenvalues of the Hessian matrix. Third, according to the light intensity distribution of a laser line obeying a Gaussian distribution in transverse section and a constant distribution in longitudinal section, a normalized model of Hessian matrix eigenvalues for the candidate centers of the laser line is presented to balance reasonably the two eigenvalues that indicate the variation tendencies of the second-order partial derivatives of the Gaussian function and constant function, respectively. The proposed model integrates a Gaussian recognition function and a sinusoidal recognition function. The Gaussian recognition function estimates the characteristic that one eigenvalue approaches zero, and enhances the sensitivity of the decision function to that characteristic, which corresponds to the longitudinal direction of the laser line. The sinusoidal recognition function evaluates the feature that the other eigenvalue is negative with a large absolute value, making the decision function more sensitive to that feature, which is related to the transverse direction of the laser line. In the proposed model the decision function is weighted for higher values to the real centers synthetically, considering the properties in the longitudinal and transverse directions of the laser line. Moreover, this method provides a decision value from 0 to 1 for arbitrary candidate centers, which yields a normalized measure for different laser lines in different images. The normalized results of pixels close to 1 are determined to be the real centers by progressive scanning of the image columns. Finally, the zero point of a second-order Taylor expansion in the eigenvector's direction is employed to refine further the extraction results of the central points at the subpixel level. The experimental results show that the method based on this normalization model accurately extracts the coordinates of laser line centers and obtains a higher recognition rate in two group experiments.
Kim, Byung-Ki;Kim, Sang-Keun;Cha, Seon-Hwa;Choi, Jun-Gu;Lee, Jun;Kim, Min-Woo;Kim, Sun-Bae;Kim, Gyeong-Sun
Korean Journal of Digital Imaging in Medicine
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v.9
no.2
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pp.17-21
/
2007
The purpose to recognize change of average pixel value of acquisition image by control panel's density and right set up method of speed (sensitivity) and exposure dose(mAs) change that dose in purpose digital flatpanel-detector. X -ray generator DHF-158H2(Hitachi, Japan). Detector CXDI 4OG(Canon, Japan), 12 : 1 grid and exposure ray 135 kVp, 250 mA, 10 ms. focus-detector distance 180 cm and used AEC mode. DICOM reflex analysis program used image J that is digital reflex analysis program that offer in United States America National Health Center(National Institutes of Health : NlH) phantom used chest phantom(Anthromorphic : Flukebrome.medicaI USA). An experiment chest phantom that consist by formation equivalence material use because density value( -3${\sim}$+3) in X-ray control panel and seep that is speed step(slow, medium, fast) each control experimentalize. image analysis reflex neted through an experiment using image j each image compare. These was change in dose according to slow, medium, fast and density's change in an experiment result. According to detector sensitivity and density condition set, dose was relationship dissimilarity 500% from 200%. The dose came highest when is density +3 to slow. and dose more increases gray scale's extent could know that rise. Could know whether how equipment set is important through this experiment. cause of disease which change by digital radiography system forward is thought to increase more, it is considered that suitable education by this and continuous interest about equipment need absolutely.
The purpose of this study was to redefine the cephalometric landmarks in three-dimensional (3D) images, which are used in orthodontic cephalometric radiography, and to evaluate the reproducibility of each landmark for 3D cephalometric analysis. Eighteen CT scans were taken at the Department of Diagnostic Radiology at Seoul National University Dental Hospital and manipulated with V works 4.0(Cybermed Inc., Seoul, Korea). The coordinate system was established using 7 reference points, with no more than 4 points on the same plane. These 7 points were generated as a volume model, the voxel size of which was 4 by 4 by 2 (threshold value=639). The cephalometric landmarks were selected at the multiplanar reformation (MPR) window on the volume mode of V works 4.0. The selected landmarks were exported to V surgery (Cybermed Inc., Seoul, Korea) for the calculation of coordinate values. All the data were taken twice with a lapse of 2 weeks by one investigator The reproducibility of each landmark was $0.17\~1.21mm$ in the x axis, $0.30\~1.53mm$. In the y axis, and $0.27\~1.81mm$ in the z axis. In all three axes, the range of error was similar. These error ranges were acceptable with regards to the pixel space and slice thickness. The most reproducible points were 1 points which were selected on the basis of the volume model. The least reproducible points were J points that were defined by sutures.
Journal of the Institute of Electronics Engineers of Korea SC
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v.49
no.4
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pp.17-22
/
2012
Convolution filtering methods have been widely applied to various digital signal processing fields for image blurring, sharpening, edge detection, and noise reduction, etc. According to their application purpose, the filter mask size or shape and the mask value are selected in advance, and the designed filter is applied to input image for the convolution processing. In this paper, we proposed an image processing acceleration method for the convolution processing by using two-dimensional Look-up table (LUT) and overlap-region buffering technique. First, based on the fixed convolution mask value, the multiplication operation between 8 or 10 bit pixel values of the input image and the filter mask values is performed a priori, and the results memorized in LUT are referred during the convolution process. Second, based on symmetric structural characteristics of the convolution filters, inherent duplicated operation region is analysed, and the saved operation results in one step before in the predefined memory buffer is recalled and reused in current operation step. Through this buffering, unnecessary repeated filter operation on the same regions is minimized in sequential manner. As the proposed algorithms minimize the computational amount needed for the convolution operation, they work well under the operation environments utilizing embedded systems with limited computational resources or the environments of utilizing general personnel computers. A series of experiments under various situations verifies the effectiveness and usefulness of the proposed methods.
The purpose of this study was to investigate image differences between KVCT vs MVCT depending on a high densities metal included in the phantom and to analyze the r values for the purpose of the dose differences between each methods. We verified the possibilities for clinical indications that using MVCT is available for the radiation therapy treatment planning. Cheese phantom was used to get a density table for each CT and CT sinogram data was transferred to radiation planning computer through DICOM_RT. Using this data, the treatment dose plan has been calculated in RTP system. We compared the differences of r values between calculated and measured values, and then applied this data to the real patient's treatment planning. The contrast of MVCT image was superior to KVCT. In KVCT, each pixel which has more than 3.0 of density was difficult to be differentiated, but in MVCT, more than 5.0 density of pixels were distinguished clearly. With the normal phantom, the percentage of the case which has less than 1($r\leq1$, acceptable criteria) of gamma value, was 94.92% for KVCT and 93.87% for MVCT. But with the cheese phantom, which has high density plug, the percentage was 88.25% for KVCT and 93.77% for MVCT respectively. MVCT has many advantages than KVCT. Especially, when the patient has high density metal, such as total hip arthroplasty, MVCT is more efficient to define the anatomical structure around the high density implants without any artifacts. MVCT helps to calculate the treatment dose more accurately.
Kim, Jin Kyem;Yoon, Haesung;Lee, Mi-Jung;Kim, Myung-Joon;Han, Kyunghwa;Koh, Hong;Kim, Seung;Han, Seok Joo;Shin, Hyun Joo
Investigative Magnetic Resonance Imaging
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v.23
no.3
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pp.251-258
/
2019
Purpose: To assess the feasibility of the use of spin-echo echo-planar imaging (SE-EPI) magnetic resonance elastography (MRE) in livers of children and young adults. Materials and Methods: Patients (${\leq}20$ years old) who underwent 3T SE-EPI MRE were included retrospectively. Subjects were divided into three groups according to the purpose of the liver MRI: suspicion of fatty liver or focal fat deposition in the liver (FAT group), liver fibrosis after receiving a Kasai operation from biliary atresia (BA group), and hepatic iron deposition after receiving chemotherapy or transfusions (IRON group). Technical failure of MRE was defined when a stiffness map showed no pixel value with a confidence index higher than 95%, and the patients were divided as success and failure groups accordingly. Clinical findings including age, gender, weight, height, and body mass index and magnetic resonance imaging results including proton density fat fraction (PDFF), $T2^*$, and MRE values were assessed. Factors affecting failure of MRE were evaluated and the image quality in wave propagation image and stiffness map was evaluated using the appropriate scores. Results: Among total 240 patients (median 15 years, 211 patients in the FAT, 21 patients in the BA, and 8 patients in the IRON groups), technical failure was noted in six patients in the IRON group (6/8 patients, 75%), while there were no failures noted in the FAT and BA groups. These six patients had $T2^*$ values ranging from 0.9 to 3.8 ms. The image quality scores were not significantly different between the FAT and BA groups (P > 0.999), while the scores were significantly lower in the IRON group (P < 0.001). Conclusion: The 3T SE-EPI MRE in children and young adults had a high technical success rate. The technical failure was occurred in children with decreased $T2^*$ value (${\leq}3.8ms$) from iron deposition.
In this study, four algorithms (Soft, Standard, Detail, Bone) were used for general CT scan (Before MAR) images and MAR (After MAR) images for patients with metal implants inserted into the hip joint. was applied to compare and analyze Noise, SNR, and CNR to find out the optimal algorithm for quantitative evaluation. As the analysis method, Image J program, which can calculate image analysis and area and pixel values on the image reconstructed with four algorithms, was used. In order to obtain Noise, SNR, and CNR, the HU mean value and HU SD value were obtained by designating the bone (ischium) closest to the metal implant in the image for the measurement site, and the background noise was the surrounding muscle. The region of interest (ROI) was equally designated as 15 × 15 mm in consideration of the size of the bone, and the values of SNR and CNR were calculated according to the given equation. As a result, for noise, After MAR and Soft algorithms showed the lowest noise, and SNR and CNR showed the highest for Before MAR and Soft algorithms. Therefore, the soft algorithm is judged to be the most appropriate algorithm for metal implant hip joint CT.
In this study, four algorithms (Standard, Bone, Dual volume, and Stent Follow up) were applied to the image of the aneurysm in cerebral angiography to reconstruct the image in 3D, and quantitatively evaluate Noise, SNR, and CNR based on the reconstructed image to find out the optimal algorithm. As an analysis method, Image J program, which can analyze images and calculate area and pixel values, was used for images reconstructed with four algorithms. In order to obtain Noise, SNR, and CNR, the region of interest (ROI) is measured by designating the point where the abnormal artery (aneurysm) is located and the surrounding normal artery in the image are measured, and the mean value and SD value are obtained. Background noise was set to two surrounding normal artery to increase reliability. The values of SNR and CNR were calculated based on the given formula. As a result, the noise was the lowest in the stent follow-up algorithm, and the SNR and CNR were the highest. Therefore, the stent follow-up algorithm is judged to be the most appropriate algorithm. The data of this study are expected to be useful as basic data for 3D image evaluation of the vascular and aneurysm in cerebral angiography, and it is believed that appropriate algorithm changes will serve as an opportunity to further improve image quality.
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