• Investigative Magnetic Resonance Imaging
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• v.9 no.2
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• pp.109-116
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• 2005

Purpose : To determine the usefulness of additional Mn-DPDP MRI for preoperative evaluation of the patients with colorectal cancers by comparison of dual-phase CT scan, Mn-DPDP enhanced MRI and combination of CT and MRI. Materials and Methods : Fifty-three colorectal cancer patients with 92 metastatic nodules underwent dualphase (arterial and portal) helical CT scan and Mn-DPDP MRI prior to surgery. The indication of MRI was presence or suspected of having metastatic lesions at CT scan and/or increased serum carcinoembryonic antigen (CEA) levels (10 ng/mL or more). The diagnosis was established by the combination of findings at surgery, intraoperative ultrasonography, and histopathologic examination. Two radiologists interpreted CT, MRI, and combination of CT-MRI at discrete sessions and evaluated each lesion for location, size, and intrinsic characteristics. The lesions were divided into three groups according to their diameter; 1cm<, 1-2 cm, and >2 cm. Diagnostic accuracy was evaluated using the alternative-free response receiver operating characteristic method. Detection and false positive rate were also evaluated. Results : In the lesions smaller than 1 cm, detection rate of combined CT-MRI was superior to CT or MRI alone (82%, p=0.036). The mean accuracy (Az values) of combined CT and MRI was significantly higher than that of CT in the lesions smaller than 2 cm (1 cm<, p=0.034; 1-2 cm, p=0.045). However, there was no significant difference between MRI and combined CT-MRI. The false positive rate of CT was higher than those of combined CT-MR in the lesions smaller than 1 cm (28%, p=0.023). Conclusion : Additional MRI using Mn-DPDP besides routine CT scan was helpful in differentiating the hepatic lesions (<2 cm) and could improve detection of the small hepatic metastases (<1 cm) from colorectal carcinoma.

• Sleep Medicine and Psychophysiology
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• v.1 no.1
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• pp.60-67
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• 1994

Objectives: The Obstructive sleep apnea syndrome is characterized by snoring, observed apnea during sleep and excessive daytime sleepiness. The overnight polysomnographic recording is used to investigate patients with possible obstructive sleep apnea syndrome. But the overnight polysomnographic recording is time consuming, expensive, and labor-intensive. Recently in diagnosis of obstructive sleep apnea syndrome, several simple screening tests have been suggested. Methods: This study was performed to assess the probability of application of clinical features and the degree of oxygen desaturation as a screening test for the obstructive sleep apnea syndrome. The sensitivity and specificity of the self-report of clinical features including snoring, observed apnea during sleep, excessive daytime sleepiness and insomnia were tested. And the degree of oxygen desaturation measured by oximetry in 42 subjects were compared with the overnight polysomnographic recording results. Results: In the prediction of apnea index more than 5, the sensitivity of observed apnea during sleep, snoring, excessive daytime sleepiness and insomnia were 96.8%, 93.5%, 38.7%, 25.8% and the specificity of those clinical features were 182%, 36.4%, 100%, 72.7%, respectively. In the prediction of apnea index more than 5, the sensitivity and specificity of the combination of more than three self-report clinical features were 54.8% and 90.9%. The degree of oxygen de saturation and maximal apnea duration in the group of apnea index more than 5 were significantly different from those in the group of apnea index below 5(P<0.001). And the apnea index was significantly correlated with the degree of oxygen desaturation and maximal apnea duration(P<0.001). Conclusion: These results suggest that application of clinical features alone as a screening test for the obstructive sleep apnea syndrome is inadequate because of it's high rate of false positive and false negative results. The degree of oxygen desaturation measured by oximetry is possibly applicable to screening test and follow up evaluation of treatment efficacy for the obstructive sleep apnea syndrome.

• Tuberculosis and Respiratory Diseases
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• v.81 no.4
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• pp.330-338
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• 2018

Background: We developed an additional laser guidance system to improve the efficacy and safety of conventional computed tomography (CT)-guided percutaneous transthoracic needle biopsy (PTNB), and we conducted this study to evaluate the efficacy and safety of our system. Methods: We retrospectively analyzed the medical records of 244 patients who underwent CT-guided PTNB using our additional laser guidance system from July 1, 2015, to January 20, 2016. Results: There were nine false-negative results among the 238 total cases. The sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of our system for diagnosing malignancy were 94.4% (152/161), 100% (77/77), 100% (152/152), 89.5% (77/86), and 96.2% (229/238), respectively. The results of univariate analysis showed that the risk factors for a false-negative result were male sex (p=0.029), a final diagnosis of malignancy (p=0.033), a lesion in the lower lobe (p=0.035), shorter distance from the skin to the target lesion (p=0.003), and shorter distance from the pleura to the target lesion (p=0.006). The overall complication rate was 30.5% (74/243). Pneumothorax, hemoptysis, and hemothorax occurred in 21.8% (53/243), 9.1% (22/243), and 1.6% (4/243) of cases, respectively. Conclusion: The additional laser guidance system might be a highly economical and efficient method to improve the diagnostic efficacy and safety of conventional CT-guided PTNB even if performed by inexperienced pulmonologists.

• Clinical and Experimental Pediatrics
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• v.57 no.6
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• pp.278-286
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• 2014

Purpose: To evaluate the potential utility of $^{123}I$-metaiodobenzylguanine ($^{123}I$-MIBG) scintigraphy and $^{18}F$-fluorodeoxyglucose ($^{18}F$-FDG) positron emission tomography (PET) for the detection of primary and metastatic lesions in pediatric neuroblastoma (NBL) patients, and to determine whether $^{18}F$-FDG PET is as beneficial as $^{123}I$-MIBG imaging. Methods: We selected 8 NBL patients with significant residual mass after operation and who had paired $^{123}I$-MIBG and $^{18}F$-FDG PET images that were obtained during the follow-up. We retrospectively reviewed the clinical charts and the findings of 45 paired scans. Results: Both scans correlated relatively well with the disease status as determined by standard imaging modalities during follow-up; the overall concordance rates were 32/45 (71.1%) for primary tumor sites and 33/45 (73.3%) for bone-bone marrow (BM) metastatic sites. In detecting primary tumor sites, $^{123}I$-MIBG might be superior to $^{18}F$-FDG PET. The sensitivity of $^{123}I$-MIBG and $^{18}F$-FDG PET were 96.7% and 70.9%, respectively, and their specificity were 85.7% and 92.8%, respectively. $^{18}F$-FDG PET failed to detect 9 true NBL lesions in 45 follow-up scans (false negative rate, 29%) with positive $^{123}I$-MIBG. For bone-BM metastatic sites, the sensitivity of $^{123}I$-MIBG and $^{18}F$-FDG PET were 72.7% and 81.8%, respectively, and the specificity were 79.1% and 100%, respectively. $^{123}I$-MIBG scan showed higher false positivity (20.8%) than $^{18}F$-FDG PET (0%). Conclusion: $^{123}I$-MIBG is superior for delineating primary tumor sites, and $^{18}F$-FDG PET could aid in discriminating inconclusive findings on bony metastatic NBL. Both scans can be complementarily used to clearly determine discrepancies or inconclusive findings on primary or bone-BM metastatic NBL during follow-up.

• Journal of Radiation Protection and Research
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• v.38 no.4
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• pp.214-227
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• 2013

Computed tomographic scan as a screening procedures in asymptomatic individuals has seen a steady increase with the introduction of multiple-raw detector CT scanners. This report provides a brief review of the current controversy surrounding CT cancer screening, with a focus on the radiation induced cancer risks and clinical efficacy. 1. A large study of patients at high risk of lung cancer(the National Lung Screening Trial[NLST]) showed that CT screening reduced cancer deaths by 20%(1.33% in those screened compared with 1.67% in those not screened). The rate of positive screening tests was 24.2% and 96.4% of the positive screening results in the low-dose CT group were false-positive. Radiation induced lung cancer risk was estimated the most important in screening population because ERR of radiation induced lung cancer does not show the decrease with increasing age and synergistic connection between smoking and radiation risk. Therefore, the radiation risk may be on the same order of magnitude as the benefit observed in the NLST. Optimal screening strategy remain uncertain, CT lung cancer screening is not yet ready for implementation. 2. Computed tomographic colonography is as good as colonoscopy for detecting colon cancer and is almost as good as colonoscopy for detecting advanced adenomas, but significantly less sensitive and specific for smaller lesions and disadvantageous for subsequent therapeutic optical colonoscopy if polyps are detected. The average effective dose from CT colonography was estimated 8-10 $mS{\nu}$, which could be a significant dose if administered routinely within the population over many years. CT colonography should a) achieve at least 90% sensitivity and specificity in the size category from 6 and 10 mm, b) offer non-cathartic bowl preparation and c) be optimized and standardized CT parameters if it is to be used for mass screening. 3. There is little evidence that demonstrates, for whole-body scanning, the benefit outweighs the detriment. This test found large portion of patient(86~90.8%) had at least one abnormal finding, whereas only 2% were estimated to have clinically significant disease. Annual scans from ages 45 to 75 years would accrue an estimated lifetime cancer mortality risk of 1.9%. There is no group within the medical community that recommends whole-body CT. No good studies indicate the accuracy of screening CT, at this time. The benefit/risk balance for any of the commonly suggested CT screening techniques has yet to be established. These areas need further research. Therefore wild screening should be avoided.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.67-73
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• 2015

In a distribution of digital image, there is a serious problem that is the image alteration by a forger. For the problem solution, this paper proposes the forensic decision algorithm of a median filtering (MF) image using the feature vector based on a coefficient of variation (c.v.) of Fourier transform. In the proposed algorithm, we compute Fourier transform (FT) coefficients of row and column line respectively of an image first, then c.v. between neighboring lines is computed. Subsquently, 10 Dim. feature vector is defined for the MF detection. On the experiment of MF detection, the proposed scheme is compared to MFR (Median Filter Residual) and Rhee's MF detection schemes that have the same 10 Dim. feature vector both. As a result, the performance is excellent at Unaltered, JPEG (QF=90), Down scaling (0.9) and Up scaling (1.1) images, and it showed good performance at Gaussian filtering ($3{\times}3$) image. However, in the performance evaluation of all measured items of the proposed scheme, AUC (Area Under ROC (Receiver Operating Characteristic) Curve) by the sensitivity and 1-specificity approached to 1 thus, it is confirmed that the grade of the performance evaluation is rated as 'Excellent (A)'.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.7
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• pp.3123-3129
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• 2016

Background: Cancer is the fourth leading cause of death in Sabah Malaysia with a reported age-standardized incidence rate was 104.9 per 100,000 in 2007. The incidence rate depends on non-mandatory notification in the registry. Under-reporting will provide the false picture of cancer control program effectiveness. The present study was to evaluate the performance of the cancer registry system in terms of representativeness, data quality, simplicity, acceptability and timeliness and provision of recommendations for improvement. Materials and Methods: The evaluation was conducted among key informants in the National Cancer Registry (NCR) and reporting facilities from Feb-May 2012 and was based on US CDC guidelines. Representativeness was assessed by matching cancer case in the Health Information System (HIS) and state pathology records with those in NCR. Data quality was measured through case finding and re-abstracting of medical records by independent auditors. The re-abstracting portion comprised 15 data items. Self-administered questionnaires were used to assess simplicity and acceptability. Timeliness was measured from date of diagnosis to date of notification received and data dissemination. Results: Of 4613 cancer cases reported in HIS, 83.3% were matched with cancer registry. In the state pathology centre, 99.8% was notified to registry. Duplication of notification was 3%. Data completeness calculated for 104 samples was 63.4%. Registrars perceived simplicity in coding diagnosis as moderate. Notification process was moderately acceptable. Median duration of interval 1 was 5.7 months. Conclusions: The performances of registry's attributes are fairly positive in terms of simplicity, case reporting sensitivity, and predictive value positive. It is moderately acceptable, data completeness and inflexible. The usefulness of registry is the area of concern to achieve registry objectives. Timeliness of reporting is within international standard, whereas timeliness to data dissemination was longer up to 4 years. Integration between existing HIS and national registration department will improve data quality.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.79-84
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• 2015

In a distribution of digital image, there is a serious problem that is a distribution of the altered image by a forger. For the problem solution, this paper proposes a median filtering (MF) image forensic decision algorithm using a feature vector according to the pixel value's gradients. In the proposed algorithm, AR (Autoregressive) coefficients are computed from pixel value' gradients of original image then 1th~6th order coefficients to be six feature vector. And the reconstructed image is produced by the solution of Poisson's equation with the gradients. From the difference image between original and its reconstructed image, four feature vector (Average value, Max. value and the coordinate i,j of Max. value) is extracted. Subsequently, Two kinds of the feature vector combined to 10 Dim. feature vector that is used in the learning of a SVM (Support Vector Machine) classification for MF (Median Filtering) detector of the altered image. On the proposed algorithm of the median filtering detection, compare to MFR (Median Filter Residual) scheme that had the same 10 Dim. feature vectors, the performance is excellent at Unaltered, Averaging filtering ($3{\times}3$) and JPEG (QF=90) images, and less at Gaussian filtering ($3{\times}3$) image. However, in the measured performances of all items, AUC (Area Under Curve) by the sensitivity and 1-specificity is approached to 1. Thus, it is confirmed that the grade evaluation of the proposed algorithm is 'Excellent (A)'.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.112-118
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• 2009

Skin color segmentation techniques have been widely utilized for face/hand detection and tracking in many applications such as a diagnosis system using facial information, human-robot interaction, an image retrieval system. In case of a video image, it is common that the skin color model for a target is updated every frame for the robust target tracking against illumination change. As for a single image, however, most of studies employ a fixed skin color model which may result in low detection rate or high false positive errors. In this paper, we propose a novel method for effective skin color segmentation in a single image, which modifies the conditions for skin color segmentation iteratively by the image feedback of segmented skin color region in a given image.