• Progress in Medical Physics
• /
• v.25 no.4
• /
• pp.271-280
• /
• 2014

Recently, digital breast tomosynthesis (DBT) has been investigated to overcome the limitation of conventional mammography for overlapping anatomical structures and high patient dose with cone-beam computed tomography (CBCT). However incomplete sampling due to limited angle leads to interference on the neighboring slices. Many studies have investigated to reduce artifacts such as interference. Moreover, appropriate filters for tomosynthesis have been researched to solve artifacts resulted from incomplete sampling. The primary purpose of this study is finding appropriate filter scheme with FBP reconstruction for DBT system to reduce artifacts. In this study, we investigated characteristics of various filter schemes with simulation and prototype digital breast tomosynthesis under same acquisition parameters and conditions. We evaluated artifacts and noise with profiles and COV (coefficinet of variation) to study characteristic of filter. As a result, the noise with parameter 0.25 of Spectral filter reduced by 10% in comparison to that with only Ramp-lak filter. Because unbalance of information reduced with decreasing B of Slice thickness filter, artifacts caused by incomplete sampling reduced. In conclusion, we confirmed basic characteristics of filter operations and improvement of image quality by appropriate filter scheme. The results of this study can be utilized as base in research and development of DBT system by providing information that is about noise and artifacts depend on various filter schemes.

• Investigative Magnetic Resonance Imaging
• /
• v.19 no.1
• /
• pp.19-30
• /
• 2015

Purpose: A new compressed sensing technique by iterative truncation of small transformed coefficients (ITSC) is proposed for fast cardiac CINE MRI. Materials and Methods: The proposed reconstruction is composed of two processes: truncation of the small transformed coefficients in the r-f domain, and restoration of the measured data in the k-t domain. The two processes are sequentially applied iteratively until the reconstructed images converge, with the assumption that the cardiac CINE images are inherently sparse in the r-f domain. A novel sampling strategy to reduce the normalized mean square error of the reconstructed images is proposed. Results: The technique shows the least normalized mean square error among the four methods under comparison (zero filling, view sharing, k-t FOCUSS, and ITSC). Application of ITSC for multi-slice cardiac CINE imaging was tested with the number of slices of 2 to 8 in a single breath-hold, to demonstrate the clinical usefulness of the technique. Conclusion: Reconstructed images with the compression factors of 3-4 appear very close to the images without compression. Furthermore the proposed algorithm is computationally efficient and is stable without using matrix inversion during the reconstruction.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.9
• /
• pp.849-854
• /
• 2001

GTM(Generative Topographic Mapping) model is a probabilistic version of the SOM(Self Organizing Maps) which was proposed by T. Kohonen. The GTM is modelled by latent or hidden variables of probability distribution of data. It is a unique characteristic not implemented in SOM model, and, therefore, it is possible with GTM to analyze data accurately, thereby overcoming the limits of SOM. In the present investigation we proposed a BGTM(Bayesian GTM) combined with Bayesian learning and GTM model that has a small mis-classification ratio. By combining fast calculation ability and probabilistic distribution of data of GTM with correct reasoning based on Bayesian model, the BGTM model provided improved results, compared with existing models.

• Communications for Statistical Applications and Methods
• /
• v.29 no.5
• /
• pp.547-559
• /
• 2022

For a chi-squared test, which is a statistical method used to test the independence of a contingency table of two factors, the expected frequency of each cell must be greater than 5. The percentage of cells with an expected frequency below 5 must be less than 20% of all cells. However, there are many cases in which the regional expected frequency is below 5 in general small area studies. Even in large-scale surveys, it is difficult to forecast the expected frequency to be greater than 5 when there is small area estimation with subgroup analysis. Another statistical method to test independence is to use the Bayes factor, but since there is a high ratio of data dependency due to the nature of the Bayesian approach, the low expected frequency tends to decrease the precision of the test results. To overcome these limitations, we will borrow information from areas with similar characteristics and pool the data statistically to propose a pooled Bayes test of independence in target areas. Jo et al. (2021) suggested hierarchical Bayesian pooling models for small area estimation of categorical data, and we will introduce the pooled Bayes factors calculated by expanding their restricted pooling model. We applied the pooled Bayes factors using bone mineral density and body mass index data from the Third National Health and Nutrition Examination Survey conducted in the United States and compared them with chi-squared tests often used in tests of independence.

• Journal of The Korean Astronomical Society
• /
• v.49 no.6
• /
• pp.255-259
• /
• 2016

We estimate the fractal dimension of the ${\rho}$ Ophiuchus Molecular Cloud Complex, associated with star forming regions. We selected a cube (${\upsilon}$, l, b) database, obtained with J = 1-0 transition lines of $^{12}CO$ and $^{13}CO$ at a resolution of 22" using a multibeam receiver system on the 14-m telescope of the Five College Radio Astronomy Observatory. Using a code developed within IRAF, we identified slice-clouds with two threshold temperatures to estimate the fractal dimension. With threshold temperatures of 2.25 K ($3{\sigma}$) and 3.75 K ($5{\sigma}$), the fractal dimension of the target cloud is estimated to be D = 1.52-1.54, where $P{\propto}A^{D/2}$, which is larger than previous results. We suggest that the sampling rate (spatial resolution) of observed data must be an important parameter when estimating the fractal dimension, and that narrower or wider dispersion around an arbitrary fit line and the intercepts at NP = 100 should be checked whether they relate to firms noise level or characteristic structure of the target cloud. This issue could be investigated by analysing several high resolution databases with different quality (low or moderate sensitivity).

• Journal of KIISE:Software and Applications
• /
• v.30 no.7_8
• /
• pp.727-743
• /
• 2003

This paper proposes an automatic highlight building algorithm for soccer video by using the structural characteristics of broadcasted sports video that an interesting (or important) event (such as goal or foul) in sports video has a continuous replay shot surrounded by gradual shot change effect like wipe. This shot editing rule is used in this paper to analyze the structure of broadcated soccer video and extracts shot involving the important events to build a highlight. It first uses the spatial-temporal image of video to detect wipe transition effects and zoom out/in shot changes. They are used to detect the replay shot. However, using spatial-temporal image alone to detect the wipe transition effect requires too much computational resources and need to change algorithm if the wipe pattern is changed. For solving these problems, a two-pass detection algorithm and a pixel sub-sampling technique are proposed in this paper. Furthermore, to detect the zoom out/in shot change and replay shots more precisely, the green-area-ratio and the motion energy are also computed in the proposed scheme. Finally, highlight shots composed of event and player shot are extracted by using these pre-detected replay shot and zoom out/in shot change point. Proposed algorithm will be useful for web services or broadcasting services requiring abstracted soccer video.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.4
• /
• pp.2627-2630
• /
• 2013

Background: Ovarian cancer continues to pose a major challenge to physicians and radiologists. It is the third most common gynecologic malignancy and estimated to be fifth leading cancer cause of death in women, constituting 23% of all gynecological malignancies. Multi-detector computed tomography (MDCT) appears to offer an excellent modality in diagnosing ovarian cancer based on combination of its availability, meticulous technique, efficacy and familiarity of radiologists and physicians. The aim of this study was to compute sensitivity, specificity, positive and negative predictive values and diagnostic accuracy of 64-slice MDCT in classifying ovarian masses; 95% confidence intervals were reported. Materials and Methods: We prospectively designed a cross-sectional analytical study to collect data from July 2010 to August 2011 from a tertiary care hospital in Karachi, Pakistan. A sample of 105 women aged between 15-80 years referred for 64-MDCT of abdomen and pelvis with clinical suspicion of malignant ovarian cancer, irrespective of stage of disease, were enrolled by non-probability purposive sampling. All patients who were already known cases of histologically proven ovarian carcinoma and having some contraindication to radiation or iodinated contrast media were excluded. Results: Our prospective study reports sensitivity, specificity; positive and negative predictive values with 95%CI and accuracy were computed. Kappa was calculated to report agreement among the two radiologists. For reader A, MDCT was found to have 92% (0.83, 0.97) sensitivity and 86.7% (0.68, 0.96) specificity, while PPV and NPV were 94.5% (0.86, 0.98) and 86.7% (0.63, 0.92), respectively. Accuracy reported by reader A was 90.5%. For reader B, sensitivity, specificity, PPV and NPV were 94.6% (0.86, 0.98) 90% (0.72, 0.97) 96% (0.88, 0.99) and 87.1% (0.69, 0.95) respectively. Accuracy computed by reader B was 93.3%. Excellent agreement was found between the two radiologists with a significant kappa value of 0.887. Conclusion: Based on our study results, we conclude MDCT is a reliable imaging modality in diagnosis of ovarian masses accurately with insignificant interobserver variability.

• The KIPS Transactions:PartA
• /
• v.11A no.7 s.91
• /
• pp.555-562
• /
• 2004

Both global volume reduction and local shape changes of hippocampus within the brain indicate their abnormal neurological states. Hippocampal shape analysis consists of two main steps. First, construct a hippocampal shape representation model ; second, compute a shape similarity from this representation. This paper proposes a novel method for the analysis of hippocampal shape using integrated Octree-based representation, containing meshes, voxels, and skeletons. First of all, we create multi-level meshes by applying the Marching Cube algorithm to the hippocampal region segmented from MR images. This model is converted to intermediate binary voxel representation. And we extract the 3D skeleton from these voxels using the slice-based skeletonization method. Then, in order to acquire multiresolutional shape representation, we store hierarchically the meshes, voxels, skeletons comprised in nodes of the Octree, and we extract the sample meshes using the ray-tracing based mesh sampling technique. Finally, as a similarity measure between the shapes, we compute $L_2$ Norm and Hausdorff distance for each sam-pled mesh pair by shooting the rays fired from the extracted skeleton. As we use a mouse picking interface for analyzing a local shape inter-actively, we provide an interaction and multiresolution based analysis for the local shape changes. In this paper, our experiment shows that our approach is robust to the rotation and the scale, especially effective to discriminate the changes between local shapes of hippocampus and more-over to increase the speed of analysis without degrading accuracy by using a hierarchical level-of-detail approach.