• Journal of Biomedical Engineering Research
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• v.11 no.2
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• pp.227-232
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• 1990

As a part of the study on ultrasonic tissue characterization, conventional ultrasonic imaging system is interfaced to the personal computer to acquire raw ultrasonic signal. One approach for tissue charaterization is performed using the attenuation map to the conventional images and the resulting attenuation map images are compared and inspected inside the region of interest from the viewpoint of pattern analysis. Currently, these methods are applied and modified to effectively find out the differences between the normal control and the patients with liver cirrhosis.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.2
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• pp.149-163
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• 1994

A novel method of dimensional measurement using machine vision, which is called Landmark Tracking System, has been developed. Its advantages come form tracking only the bright, standard shaped "landmarks" which are made from retroreflective sheets. In the design of the LTS, it is essential to know the relationship between optical parameters and their influence on system performance. Such optical parameters include the brightness of landmark image, the illumination system design, and the choice of imaging optics. And the performance of retroreflective material also plays important role in the LTS performances. Influences of such optical parameters on LTS's dimensional measurement characteristics are investigated, with respect to the retroreflective material, the imaging optics, and the illumination system. Measuremtn errors due to parameter variations are also analyzed. Experiments are performed with a LTS prototype. Retroreflective characteristics are verified, and the LTS's measurement performances are measured in the form of repeatability and accuracy. Experimental results shgow that the LTS has repeatability better than 1/30,000 of a field of view(30 degrees), and accuracy better tha 1/3,000 of a field fo view.d fo view.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.11
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• pp.200-208
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• 2004

In ultrasonic bone densitometry, the positioning of measurement site is decisive in precision and reproducibility. In this study, automatic Region of Interest (ROI) detection algorithm is suggested and adopted the method using the local minimum value by ultrasonic image. The preprocess before the local minimum method extracts out the bone area and calculates the geometrical information of bone. The developed ROI detection algorithm was applied to the clinical test for the subject of 305 female patients in the range of 22-88 years old. As the results, the accuracy of the algorithm was shown to be 98.3％. It was also found that bone density parameter was significantly correlated with age(r=0.85, p<0.0001).

• Current Optics and Photonics
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• v.4 no.1
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• pp.1-8
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• 2020

We research a system of compressed-sensing computational ghost imaging (CSCGI) based on the intensity fluctuation brought by turbulence. In this system, we used the gamma-gamma intensity-fluctuation model, which is commonly used in transmission systems, to simulate the CSCGI system. By setting proper values of the parameters such as transmission distance, refractive-index structure parameter, and sampling rates, the peak signal-to-noise ratio (PSNR) performance and bit-error rate (BER) performance are obtained to evaluate the imaging quality, which provides a theoretical model to further research the ghost-imaging algorithm.

• Investigative Magnetic Resonance Imaging
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• v.24 no.3
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• pp.123-131
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• 2020

Purpose: Joint label fusion (JLF) is a popular multi-atlas-based segmentation algorithm, which compensates for dependent errors that may exist between atlases. However, in order to get good segmentation results, it is very important to set the several free parameters of the algorithm to optimal values. In this study, we first investigate the feasibility of a JLF algorithm for prostate segmentation in MR images, and then suggest the optimal set of parameters for the automatic prostate segmentation by validating the results of each parameter combination. Materials and Methods: We acquired T2-weighted prostate MR images from 20 normal heathy volunteers and did a series of cross validations for every set of parameters of JLF. In each case, the atlases were rigidly registered for the target image. Then, we calculated their voting weights for label fusion from each combination of JLF's parameters (r_pxy, r_pz, r_sxy, r_sz, β). We evaluated the segmentation performances by five validation metrics of the Prostate MR Image Segmentation challenge. Results: As the number of voxels participating in the voting weight calculation and the number of referenced atlases is increased, the overall segmentation performance is gradually improved. The JLF algorithm showed the best results for dice similarity coefficient, 0.8495 ± 0.0392; relative volume difference, 15.2353 ± 17.2350; absolute relative volume difference, 18.8710 ± 13.1546; 95% Hausdorff distance, 7.2366 ± 1.8502; and average boundary distance, 2.2107 ± 0.4972; in parameters of r_pxy = 10, r_pz = 1, r_sxy = 3, r_sz = 1, and β = 3. Conclusion: The evaluated results showed the feasibility of the JLF algorithm for automatic segmentation of prostate MRI. This empirical analysis of segmentation results by label fusion allows for the appropriate setting of parameters.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.5
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• pp.484-493
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• 2012

Since the 1980s, there have been many research activities devoted to quantitatively characterizing and imaging human tissues based on sound speed, attenuation coefficient, density, nonlinear B/A parameter, etc., but those efforts have not yet reached the stage of commercialization. However, a new imaging technology termed elastography, which was proposed in the early 1980s, has recently been implemented in commercial clinical ultrasound scanners, and is now being used to diagnose prostates, breasts, thyroids, livers, blood vessels, etc., more quantitatively as a complementary adjunct modality to the conventional B-mode imaging. The purpose of this article is to introduce and review various elastographic algorithms for use in quasistatic or static compression type elasticity imaging modes. Most of the algorithms are based on the crosscorrelation or autocorrelation function methods, and the fundamental difference is that the time shift is estimated by changing the lag variable in the former, while it is directly obtained from the phase shift at a fixed lag in the latter.

• Journal of IKEEE
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• v.19 no.1
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• pp.33-40
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• 2015

Inverse problem in electrical impedance tomography (EIT) is highly ill-posed therefore prior information is used to mitigate the ill-posedness. Regularization methods are often adopted in solving EIT inverse problem to have satisfactory reconstruction performance. In solving the EIT inverse problem, iterative Gauss-Newton method is generally used due to its accuracy and fast convergence. However, its performance is still suboptimal and mainly depends on the selection of regularization parameter. Although, there are few methods available to determine the regularization parameter such as L-curve method they are sometimes not applicable for all cases. Moreover, regularization parameter is a scalar and it is fixed during iteration process. Therefore, in this paper, a novel method is used to determine the regularization parameter to improve reconstruction performance. Conductivity norm is calculated at each iteration step and it used to obtain the regularization parameter which is a diagonal matrix in this case. The proposed method is applied to human thorax imaging and the reconstruction performance is compared with traditional methods. From numerical results, improved performance of proposed method is seen as compared to conventional methods.

• The Korean Journal of Nuclear Medicine
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• v.31 no.1
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• pp.83-89
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• 1997

About one-third of radiologically indeterminate solitary pulmonary nodules (SPN) are eventually turned out to be malignant. It is very important to noninvasively determine whether the SPN is malignant or not for the decision of its way of management. PET imaging is highlighted by its unique ability of imaging the function and metabolism of cells. Glucose metabolism is increased in malignant transformed cells. We peformed FDG-PET studies in patients who had radiologically indeterminate SPN and compared the findings with histologic diagnoses to assess the diagnostic accuracy in the detection of malignancy and to decide which parameter is the most suitable for clinical practice among peak SUV (pSUV), average SUV (aSUV), 50/10 ratio, and time-activity curve (TAC), Thirty patients were included in this study and the most useful parameter was pSUV. The sensitivity and specificity in the detection of malignant SPN using 3.5 as a cut off pSUV were both 87%. Interestingly, all 2 false-negative cases were bronch-ioloalveolar carcinoma on histologic examination. If these cases, which could be strongly suspected by CT findings, were excluded, the sensitivity of pSUV was 100%. In conclusion, PET imaging is very helpful for determining malignancy in indeterminate SPN and pSUV is a conveniently measurable parameter which is valuable for interpretation.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.12
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• pp.1916-1924
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• 1990

In this paper attenuation effect on the measurement and the tomography of nonlinear parameter is discussed. We perform computer simulation with the method using harmonic components and the method using secondary wave components, and then estimate attenuation effect through the results and compare two measurement techniques. According to simulation result the attenuation effect is more intensive as large n and \ulcorner, and the degree of the attenuation effect is represented as error functions. In the aspect of measuremnet techniques, the method using secondary wave components is more insensitive to attenuation effect than the method using harmonic compnents. We obtain the same result in the nonlinear tomography, and show that the attenuation compensive filter is required because the whole tomogram is affected by frequency dependent attenuation(or nonlinear attenuation)

• Journal of information and communication convergence engineering
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• v.5 no.3
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• pp.245-248
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• 2007

In this paper, we research the content-based analysis and classification according to the composition of the feature parameter data base for the audio data to implement the audio data index and searching system. Audio data is classified to the primitive various auditory types. We described the analysis and feature extraction method for the feature parameters available to the audio data classification. And we compose the feature parameters data base in the index group unit, then compare and analyze the audio data centering the including level around and index criterion into the audio categories. Based on this result, we compose feature vectors of audio data according to the classification categories, and simulate to classify using discrimination function.