• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.61-64
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• 2000

The purpose of this study is prove the effectiveness of an energy subtraction image for the detection of pulmonary nodules and the effectiveness of multi-resolutional filter on an energy subtraction image to detect pulmonary nodules. Also we examine influential factors to the accuracy of detection of pulmonary nodules from viewpoints of types of images and evaluation methods. As one type of images, we select energy subtraction X-ray images, at the same time is done ▽$^2$G filter and multi-resolutional filter. Here select two evaluation methods and make clear the effectiveness of multi-resolutional filter on an energy subtraction image.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.293-294
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• 2007

The purpose of this study is prove the effectiveness of an energy subtraction image for the detection of pulmonary nodules and the effectiveness of multi-resolutional filter on an energy subtraction image to detect pulmonary nodules. Also we study influential factors to the accuracy of detection of pulmonary nodules from viewpoints of types of images, types of digital filters and types of evaluation methods. As one type of images, we select an energy subtraction image, which removes bones such as ribs from the conventional X-ray image by utilizing the difference of X-ray absorption ratios at different energy between bones and soft tissue. Here we select two evaluation methods and make clear the effectiveness of multi-resolutional filter on an energy subtraction image.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3401-3408
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• 2023

In this study, we used the Monte Carlo N-Particle program to simulate the gamma-ray spectra obtained from plastic scintillators holes filled with bismuth nanoparticles. We confirmed that the incorporation of bismuth nanoparticles into a plastic scintillator enhances its performance for gamma-ray spectroscopy using the subtraction method. The subtracted energy spectra obtained from the bismuth-nanoparticle-incorporated and the original plastic scintillator exhibit a distinct energy peak that does not appear in the corresponding original spectra. We varied the diameter and depth of the bismuth-filled holes to determine the optimal hole design for gamma-ray spectroscopy using the subtraction method. We evaluated the energy resolutions of the energy peaks in the gamma-ray spectra to estimate the effects of the bismuth nanoparticles and determine their optimum volume in the plastic scintillator. In addition, we calculated the peak-to-total ratio of the energy spectrum to evaluate the energy measuring limit of the bismuth nanoparticle-containing plastic scintillator using the subtraction method.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.69-76
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• 2010

The segmentation of moving object in video sequence is a core technique of intelligent image processing system such as video surveillance, traffic monitoring and human tracking. A typical method to segment a moving region from the background is the background subtraction. The steps of background subtraction involve calculating a reference image, subtracting new frame from reference image and then thresholding the subtracted result. One of famous background modeling is Gaussian mixture model (GMM). Even though the method is known efficient and exact, GMM suffers from a problem that includes false pixels in ROI (region of interest), specifically shadow pixels. These false pixels cause fail of the post-processing tasks such as tracking and object recognition. This paper presents a method for removing false pixels included in ROT. First, we subdivide a ROI by using shape characteristics of detected objects. Then, a method is proposed to classify pixels from using histogram characteristic and comparing difference of energy that converts the color value of pixel into grayscale value, in order to estimate whether the pixels belong to moving object area or shadow area. The method is applied to real video sequence and the performance is verified.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.10
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• pp.138-142
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• 2016

Dual-energy digital radiography (DEDR) has been used for detecting lesions within the body using energy subtraction methods. The purpose of this study was to acquire optimal bone and tissue image by changing physical factors such as Tube voltage (kVp) and add filters, and then we compared with the predicted values using SRS-78 program and experimental results. For that purpose, we acquired images according to changes in physical parameters of various materials since we had to acquire the optimal bone and tissue image using energy subtraction. Used phantom consists of aluminum and polymethyl methacrylate (PMMA) and a comparison of image optimization was measured by contrast-to-noise ratio (CNR). In results, first of all, we confirmed that a subtraction image from 50 kVp image and 120 kVp image is optimal bone and tissue image. Also when we added a 10 mm Aluminum add filter, we expected it is a result of the optimal bone and tissue image. Besides, we confirmed these results are consistent with the predicted optimized condition by SRS-78 program.. In conclusion, we indicated that we can acquire optimal bone and tissue image by controling physical factors such as kVp, add filters through this study. Also we expected that DEDR will contribute to the field of medical imaging technology.

• Journal of radiological science and technology
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• v.40 no.3
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• pp.443-451
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• 2017

Mammography is commonly used for screening early breast cancer. However, mammographic images, which depend on the physical properties of breast components, are limited to provide information about whether a lesion is malignant or benign. Although a dual-energy subtraction technique decomposes a certain material from a mixture, it increases radiation dose and degrades the accuracy of material decomposition. In this study, we simulated a breast phantom using attenuation characteristics, and we proposed a technique to enable the accurate material decomposition by applying weighting factors for the dual-energy mammography based on a photon-counting detector using a Monte Carlo simulation tool. We also evaluated the contrast and noise of simulated breast images for validating the proposed technique. As a result, the contrast for a malignant tumor in the dual-energy weighted subtraction technique was 0.98 and 1.06 times similar than those in the general mammography and dual-energy subtraction techniques, respectively. However the contrast between malignant and benign tumors dramatically increased 13.54 times due to the low contrast of a benign tumor. Therefore, the proposed technique can increase the material decomposition accuracy for malignant tumor and improve the diagnostic accuracy of mammography.

• Analytical Science and Technology
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• v.13 no.4
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• pp.403-411
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• 2000

This study described a method of thermoluminescence dating of pottery shards using subtraction method. TL measurement was achieved using two different types of samples prepared by quartz inclusion method and fine-grain technique. Fine grains (size range: $5-10{\mu}m$) were separated by suspending grounded pottery samples into acetone solution and sedimentation quantitatively. In quartz inclusion method quartz grains in the size range of 90 to $125{\mu}m$ diameter were obtained by extracting the quartz crystals embed in the pottery shards and etching them with 1.0 M HF solutions. The archaeological dose of both the quartz and fine grains was determined from the dose calibration curves obtained from sequential irradiation of $^{137}Cs$ gamma and $^{241}Am$ alpha source to the samples and TL measurement of natural samples, in which the alpha dose of 4.60 Gy for the Packjae pottery was obtained using subtraction method. Annual alpha dose rates ($3.05{\pm}0.11$ mGy/yr.) were determined by the analysis of U, Th contents in the pottery shards and evaluation of the values with Bell's equation. Dividing the alpha dose accumulated in the pottery shards by the annual alpha dose rate, we found age of approximately $1508{\pm}80$ years B.P. (AD. ca. 492 yr.) for the Packjae pottery. It matches well with the archeological age estimate (middle of 5th century) within 10 percent uncertainty and thereby conforms the age of the pottery sample.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7C
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• pp.604-610
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• 2010

In this paper we proposed FSFN (Filter bank sub-band energy subtraction based CLSFN) method to improve the recognition performance of the existing CLSFN (Cepstral distance and Log-energy based Silence Feature Normalization). The proposed FSFN reduces the energy of noise components in filter bank sub-band domain when extracting the features from speech data. This leads to extract the enhanced cepstral features and thus improves the accuracy of speech/silence classification using the enhanced cepstral features. Therefore, it can be expected to get improved performance comparing with the existing CLSFN. Experimental results conducted on Aurora 2.0 DB showed that our proposed FSFN method improves the averaged word accuracy of 2% comparing with the conventional CLSFN method, and FSFN combined with CMVN (Cepstral Mean and Variance Normalization) also showed the best recognition performance comparing with others.

• Korean Journal of Digital Imaging in Medicine
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• v.3 no.1
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• pp.100-105
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• 1997

• Journal of Ocean Engineering and Technology
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• v.25 no.2
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• pp.1-6
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• 2011

Vibration-based Structural Health Monitoring (SHM) systems use field measurements of operational signals, which are distorted by noise from many sources. Reducing this noise allows a more accurate assessment of the original "clean" signal and improves analysis results. The implementation of a noise reduction methodology for the Modal Distribution Method (MDM) is reported here. The spectral subtraction method is a popular broadband noise reduction technique used in speech signal processing. Its basic principle is to subtract the magnitude of the noise from the total noisy signal in the frequency domain. The underlying assumption of the method is that noise is additive and uncorrelated with the signal. In speech signal processing, noise can be measured when there is no signal. In the MDM, however, the magnitude of the noise profile can be estimated only from the magnitude of the Power Spectral Density (PSD) at higher frequencies than the frequency range of the true signal associated with structural vibrations under the additional assumption of white noise. The implementation of the spectral subtraction method to MDM may decrease the energy of the individual mode. In this work, a modification of the spectral subtraction method is introduced that enables the conservation of the energies of individual modes. The main difference is that any (negative) bars with a height below zero after subtraction are set to the absolute value of their height. Both noise reduction methods are implemented in the MDM, and an application example is presented that demonstrates its effectiveness when used with a signal corrupted by noise.