• Korean Journal of Radiology
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• v.23 no.1
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• pp.139-149
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• 2022

Objective: To compare the effects of bone suppression imaging using deep learning (BSp-DL) based on a generative adversarial network (GAN) and bone subtraction imaging using a dual energy technique (BSt-DE) on radiologists' performance for pulmonary nodule detection on chest radiographs (CXRs). Materials and Methods: A total of 111 adults, including 49 patients with 83 pulmonary nodules, who underwent both CXR using the dual energy technique and chest CT, were enrolled. Using CT as a reference, two independent radiologists evaluated CXR images for the presence or absence of pulmonary nodules in three reading sessions (standard CXR, BSt-DE CXR, and BSp-DL CXR). Person-wise and nodule-wise performances were assessed using receiver-operating characteristic (ROC) and alternative free-response ROC (AFROC) curve analyses, respectively. Subgroup analyses based on nodule size, location, and the presence of overlapping bones were performed. Results: BSt-DE with an area under the AFROC curve (AUAFROC) of 0.996 and 0.976 for readers 1 and 2, respectively, and BSp-DL with AUAFROC of 0.981 and 0.958, respectively, showed better nodule-wise performance than standard CXR (AUAFROC of 0.907 and 0.808, respectively; p ≤ 0.005). In the person-wise analysis, BSp-DL with an area under the ROC curve (AUROC) of 0.984 and 0.931 for readers 1 and 2, respectively, showed better performance than standard CXR (AUROC of 0.915 and 0.798, respectively; p ≤ 0.011) and comparable performance to BSt-DE (AUROC of 0.988 and 0.974; p ≥ 0.064). BSt-DE and BSp-DL were superior to standard CXR for detecting nodules overlapping with bones (p < 0.017) or in the upper/middle lung zone (p < 0.017). BSt-DE was superior (p < 0.017) to BSp-DL in detecting peripheral and sub-centimeter nodules. Conclusion: BSp-DL (GAN-based bone suppression) showed comparable performance to BSt-DE and can improve radiologists' performance in detecting pulmonary nodules on CXRs. Nevertheless, for better delineation of small and peripheral nodules, further technical improvements are required.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.2
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• pp.95-102
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• 2005

There are many tube and pipeline in nuclear power plant under high temperature and high pressure. Erosion and corrosion defects were expected on these tube and pipe-line by environmental and mechanical factors. These erosion and corrosion defects ran be evaluated by ultrasonic technique. In these study, Scanning Laser Source(SLS) technique was applied to detect defect and construct image. This technique also makes detection possible on rough and curved surfaces such as tube and pipe-line by scanning. Conventional ultrasonic scanning technique requires immersion of specimen or water jet for transferring ultrasonic wave between transducer and specimen. However, this SLS technique does not need contacting and couplant to generate surface wave and to get flaw images. Therefore, this SLS technique has several advantages, for complicated production inspection, non-contact, remote from specimen, and high resolution. In this study, SLS images were obtained with various conditions of generation laser ultrasound and receiving in order to enhance detectability of flaws on the tube. Stress corrosion cracks were produced on tube and images of stress corrosion cracks were constructed by using SLS technique.

• Journal of Biosystems Engineering
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• v.24 no.6
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• pp.539-546
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• 1999

Some stress for a plant could be detected to a certain degree by plant physiological measuring technique of the state of the art. The capability of early detection of my measuring system depends on kind of plant and kind and level of stress. The objectives of this study were to evaluate the capability of several fast and intact type plant stress detection systems to detect nitrogen deficiency of cucumber in the field. A series of experiment was carried out with four kinds of intact type measuring devices - a chlorophyll content meter, a chlorophyll fluorescence measurement system, an infrared thermometer and an optical spectrometer. The experiments resulted that the chlorophyll content meter could detect the stress of N deficiency at a confidence level higher than 95% on 3rd day for the earliest case and the detection of high precision was possible from 7th day after the stress was applied. The chlorophyll fluorescence measurement system detected the stress at a confidence level higher than 95% on 3rd day for the earliest case but the detection was not as much precise as the chlorophyll content meter. Leaf temperature measurement noted very poor results to detect the stress. Using the spectrometer, sensitive wavelength regions to detect the stress were searched and found out as 562∼564 nm, 700∼724 nm and 1,886∼1,894 nm. With the spectrometer using any of wavelength within the sensitive wavelength region, detection of the stress at a confidence level higher than 95% was possible from 3rd or 4th day after the stress was applied.

• Smart Structures and Systems
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• v.21 no.5
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• pp.687-694
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• 2018

The problem of wheel tread defects has become a major challenge for the health management of high-speed rail as a wheel defect with small radius deviation may suffice to give rise to severe damage on both the train bogie components and the track structure when a train runs at high speeds. It is thus highly desirable to detect the defects soon after their occurrences and then conduct wheel turning for the defective wheelsets. Online wheel condition monitoring using wheel impact load detector (WILD) can be an effective solution, since it can assess the wheel condition and detect potential defects during train passage. This study aims to develop an FBG-based track-side wheel condition monitoring method for the detection of wheel tread defects. The track-side sensing system uses two FBG strain gauge arrays mounted on the rail foot, measuring the dynamic strains of the paired rails excited by passing wheelsets. Each FBG array has a length of about 3 m, slightly longer than the wheel circumference to ensure a full coverage for the detection of any potential defect on the tread. A defect detection algorithm is developed for using the online-monitored rail responses to identify the potential wheel tread defects. This algorithm consists of three steps: 1) strain data pre-processing by using a data smoothing technique to remove the trends; 2) diagnosis of novel responses by outlier analysis for the normalized data; and 3) local defect identification by a refined analysis on the novel responses extracted in Step 2. To verify the proposed method, a field test was conducted using a test train incorporating defective wheels. The train ran at different speeds on an instrumented track with the purpose of wheel condition monitoring. By using the proposed method to process the monitoring data, all the defects were identified and the results agreed well with those from the static inspection of the wheelsets in the depot. A comparison is also drawn for the detection accuracy under different running speeds of the test train, and the results show that the proposed method can achieve a satisfactory accuracy in wheel defect detection when the train runs at a speed higher than 30 kph. Some minor defects with a depth of 0.05 mm~0.06 mm are also successfully detected.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.9
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• pp.5519-5525
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• 2013

Background: Cervical cancer is the second most common cancer in Thai women after breast cancer. Currently, the Papanicolaou (Pap) smear is the recommended procedure for cervical cancer screening in Thailand, but only a relatively small percentage of women follow this screening program. An alternative method to detect HPV genotypes associated with cervical cancer is self-sampling of urine, which is a more widely accepted method. Our study aimed to evaluate the prevalence of HPV in Thai women using urine and cervical swabs and prevalence of HPV in Thai men using urine samples. Materials and Methods: Tumorigenic HPV detection was accomplished by electrochemical DNA chip and PCR/direct sequencing. In addition to HPV prevalence, we report the concordance between different methods and sample types. One-hundred and sixteen women and 100 men were recruited. Histological examination revealed normal cytology in 52 women, atypical squamous cells of undetermined significance (ASCUS) in 9, low-grade squamous intraepithelial lesions (LSIL) in 24, and high-grade squamous intraepithelial lesions (HSIL) in 31. One-hundred men were classified as heterosexuals (n=45) and homosexuals (n=55). Results: The most prevalent HPV genotype in our study was HPV16. The HPV detection rate was generally lower in urine samples compared with cervical samples. Overall, there was good agreement for the detection of carcinogenic HPV from female cervical samples between the DNA chip and PCR/sequencing, with 88.8% total agreement and a kappa value of 0.76. In male urine samples, the level of agreement was higher in heterosexuals compared with homosexuals. Conclusions: Further improvement is required to increase an overall yield of HPV DNA detection in urine samples before clinical application of a urine-based HPV screening program. The electrochemical DNA chip test is a promising technique for carcinogenic HPV detection.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.157-163
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• 2017

The object segmentation approach has the merit of reducing the processing cost required to detect moths of interest, because it applies a moth detection algorithm to the segmented objects after segmenting the objects individually in the moth image. In this paper, an object segmentation method for moth detection in pheromone trap images is proposed. Our method consists of preprocessing, thresholding, morphological filtering, and object labeling processes. Thresholding in the process is a critical step significantly influencing the performance of object segmentation. The proposed method can threshold very elaborately by reflecting the local properties of the moth images. We performed thresholding using global and local versions of Ostu's method and, used the proposed method for the moth images of Carposina sasakii acquired on a pheromone trap placed in an orchard. It was demonstrated that the proposed method could reflect the properties of light and background on the moth images. Also, we performed object segmentation and moth classification for Carposina sasakii images, where the latter process used an SVM classifier with training and classification steps. In the experiments, the proposed method performed the detection of Carposina sasakii for 10 moth images and achieved an average detection rate of 95% of them. Therefore, it was shown that the proposed technique is an effective monitoring method of Carposina sasakii in an orchard.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.675-686
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• 2005

In this paper, we propose an efficient face region detection technique for the content-based video summarization. To segment video, shot changes are detected from a video sequence and key frames are selected from the shots. We select one frame that has the least difference between neighboring frames in each shot. The proposed face detection algorithm detects face region from selected key frames. And then, we provide user with summarized frames included face region that has an important meaning in dramas or movies. Using Bayes classification rule and statistical characteristic of the skin pixels, face regions are detected in the frames. After skin detection, we adopt the projection method to segment an image(frame) into face region and non-face region. The segmented regions are candidates of the face object and they include many false detected regions. So, we design a classifier to minimize false lesion using CART. From SGLD matrices, we extract the textual feature values such as Inertial, Inverse Difference, and Correlation. As a result of our experiment, proposed face detection algorithm shows a good performance for the key frames with a complex and variant background. And our system provides key frames included the face region for user as video summarized information.

• Journal of the Korean Chemical Society
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• v.37 no.4
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• pp.453-461
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• 1993

Detection method was developed using a simply designed photochemical reactor made of teflon coil and low pressure mercury lamp. This method of UV photolysis of analytes followed by UV, fluorescence and electrochemical detection was found to be useful for four thiocarbamates. Analytes eluting from the column are irradiated with a high flux of 254 nm UV light, so that they change to either fluorescent active forms or highly electrochemically sensitive products. Appling this technique to the UV detection, thiocarbamates were converted into long wavelength absorbing products upon UV irradiation. In fluorescence detector four thiocarbamates are not detected at nonirradiated condition but fluorescence signals of MPTC, CPTC photolysates are appeared after irradiation with UV light. The electrochemical detection for the determination of thiocarbamates was enhanced up to 5∼20 fold signal after UV irradiation, compared to that of the nonirradiated. The detection limit of thiocarbamates on electrochemical detector was 13.3∼0.02 ng under pH 7.0, ionic strength $0.5{\times}10^{-2}$ M, phosphate buffer solution. Adducts produced by reaction of photolysates and OPA-MERC in the reaction coil were monitored at 425 nm with fluorescence detector, and one of the photolysates was primary amine.

• Parasites, Hosts and Diseases
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• v.57 no.1
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• pp.9-15
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• 2019

Melting temperature shift ($T_m-shift$) is a new detection method that analyze the melting curve on real-time PCR thermocycler using SYBR Green I fluorescent dye. To establish a $T_m-shift$ method for the detection of Ancylostoma ceylanicum and A. tubaeforme in cats, specific primers, with GC tail of unequal length attached to their 5' end, were designed based on 2 SNP loci (ITS101 and ITS296) of the internal transcribed spacer 1 (ITS1) sequences. The standard curve of $T_m-shift$ was established using the standard plasmids of A. ceylanicum (AceP) and A. tubaeforme (AtuP). The $T_m-shift$ method stability, sensitivity, and accuracy were tested with reference to the standard curve, and clinical fecal samples were also examined. The results demonstrated that the 2 sets of primers based on the 2 SNPs could accurately distinguish between A. ceylanicum and A. tubaeforme. The coefficient of variation (CV) of $T_m$- values of AceP and AtuP was 0.07% and 0.06% in ITS101 and was 0.06% and 0.08% in ITS296, respectively. The minimum detectable DNA concentration was $5.22{\times}10^{-6}$ and $5.28{\times}10^{-6}ng/{\mu}l$ samples of AceP and AtuP, respectively. The accuracy of $T_m-shift$ method reached 100% based on examination of 10 hookworm DNA samples with known species. In the clinical detection of hookworm in 69 stray cat fecal sample, the $T_m-shift$ detection results were consistent with the microscopic examination and successfully differentiated between the 2-hookworm species. In conclusion, the developed method is a rapid, sensitive and accurate technique and can provide a promising tool for clinical detection and epidemiological investigation of cat-derived hookworms.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.623-631
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• 2021

The increased transport of marine hazardous and noxious substances (HNS) has resulted in frequent HNS spill accidents domestically and internationally. There are about 6,000 species of HNS internationally, and most of them have toxic properties. When an accidental HNS spill occurs, it can destroys the marine ecosystem and can damage life and property due to explosion and fire. Constructing a spectral library of HNS according to wavelength and developing a detection algorithm would help prepare for accidents. In this study, a ground HNS spill experiment was conducted in France. The toluene spectrum was determined through hyperspectral sensor measurements. HNS present in the hyperspectral images were detected by applying the spectral mixture algorithm. Preprocessing principal component analysis (PCA) removed noise and performed dimensional compression. The endmember spectra of toluene and seawater were extracted through the N-FINDR technique. By calculating the abundance fraction of toluene and seawater based on the spectrum, the detection accuracy of HNS in all pixels was presented as a probability. The probability was compared with radiance images at a wavelength of 418.15 nm to select abundance fractions with maximum detection accuracy. The accuracy exceeded 99% at a ratio of approximately 42%. Response to marine spills of HNS are presently impeded by the restricted access to the site because of high risk of exposure to toxic compounds. The present experimental and detection results could help estimate the area of contamination with HNS based on hyperspectral remote sensing.