• Journal of Oral Medicine and Pain
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• v.30 no.4
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• pp.383-389
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• 2005

Xerostomia is defined as a subjective complaint of dry mouth that may be perceived when there is insufficient mucosal wetting. However, the diagnosis and treatment of xerostomia is not that simple because of the fact that the subjective awareness of dry mouth is not always correlated with a diminution in the flow of saliva and there is always a difference between individuals in salivary flow rates needed for normal oral function. In the present study, the aim was to develop a questionnaire to evaluate the dry mouth symptoms and to analyze its reliability and usability as a diagnostic and analytic tool for xerostomia. The questionnaire which consists of 6 Visual Analogue Scale(VAS) type questions to evaluate the subjective oral dryness and 4 questions to evaluate behavior to avoid oral dryness was developed and administered twice with 1 week's interval to the healthy 88 young adults without dry mouth symptoms(44 males and 44 females; mean age was $25.6{\pm}3.1$ years in male and $24.3{\pm}2.1$ years in female). The results were as follows. 1 The intraclass correlation coefficients of 6 questions to evaluate the subjective oral dryness were as significantly high as 0.767 for the degree of oral dryness at other times of the day, 0.850 for the amount of saliva in the mouth, and 0.791 for the degree of effect on daily life due to oral dryness and as high as 0.563 for the degree of oral dryness at night or on awakening, 0.674 for the degree of oral dryness during eating, and 0.641 for the degree of difficulty in swallowing foods. 2. Cronbach's alpha value of 6 questions was 0.982. It can be concluded that the series of questions to evaluate the subjective oral dryness has high internal consistency. 3. Cohen's kappa values of 4 questions to evaluate behavior to relieve oral dryness were as significantly high as 0.850 for the frequency of keeping a glass of water at the bedside and as high as 0.506 the frequency of awakening during sleeping due to oral dryness, 0.419 for the frequency of sipping liquids to aid in eating dry foods, and 0.407 for the frequency of using a candy or chewing gum due to oral dryness. From the results, it can be concluded that the questionnaire consisting of 6 VAS type questions to evaluate the subjective oral dryness and 4 questions to evaluate behavior to relieve oral dryness has reliability of good to excellent level, and that the series of 6 VAS type questions has significantly high internal consistency to evaluate the subjective oral dryness.

• Investigative Magnetic Resonance Imaging
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• v.18 no.3
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• pp.219-224
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• 2014

Purpose : To determine the incidence of truncated triangle appearance of anterior horn (AH) to body of medial meniscus (MM) and determine its clinical significance. Materials and Methods: IRB approval was obtained, and informed consent waived for this study. The criteria of "pseudoradial tear" was truncated triangle appearance of the tip of AH to body of MM on one or more coronal images with adjacent fluid signal intensity at the blunted tip. Two musculoskeletal radiologists retrospectively evaluated 485 knee MR images independently for the presence and number of sections with "pseudoradial tear" of AH to body of MM using proton density-weighted coronal MR images. Inter-and intraobserver agreement was calculated using kappa coefficients. Medical records were reviewed for arthroscopic correlation. Results: A pseudoradial tear in the AH to body of MM was present in 381 (78.6%) patients. Locations were 112 in AH (29.4%), 143 in AH to body (37.5%), and 126 in body (33.1%). Number of consecutive sections of pseudoradial tear were 1 in 100 (26.2%), 2 in 164 (43.0%), 3 in 94 (24.7%), 4 in 21 (5.5%), and 5 in 2 (0.5%). Interobserver agreement was 0.99 for presence and 0.43 for number of sections of pseudoradial tear. Arthroscopies were performed in 96 patients and none of the pseudoradial tears were proven as true radial tears on arthroscopy. Conclusion: Pseudoradial tears are frequently seen in AH to body of MM on coronal MR images and may be another pitfall that a radiologist needs to be aware of and be able to differentiate from true radial tear.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.43-52
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• 2016

Due to the characteristics of microwave signals, Radar satellite image has been used for flood detection without weather and time influence. The more methods of flood detection were developed, the more detection rate of flood area has been increased. Since flood causes a lot of damages, flooded area should be distinguished from non flooded area. Also, the detection of flood area should be accurate. Therefore, not only image resolution but also the filtering process is critical to minimize resolution degradation. Although a resolution of radar images become better as technology develops, there were a limited focused on a highly suitable filtering methods for flood detection. Thus, the purpose of this study is to find out the most appropriate filtering method for flood detection by comparing three filtering methods: Lee filter, Frost filter and NL-means filter. Therefore, to compare the filters to detect floods, each filters are applied to the radar image. Comparison was drawn among filtered images. Then, the flood map, results of filtered images are compared in that order. As a result, Frost and NL-means filter are more effective in removing the speckle noise compared to Lee filter. In case of Frost filter, resolution degradation occurred severly during removal of the noise. In case of NL-means filter, shadow effect which could be one of the main reasons that causes false detection were not eliminated comparing to other filters. Nevertheless, result of NL-means filter shows the best detection rate because the number of shadow pixels is relatively low in entire image. Kappa coefficient is scored 0.81 for NL-means filtered image and 0.55, 0.64 and 0.74 follows for non filtered image, Lee filtered image and Frost filtered image respectively. Also, in the process of NL-means filter, speckle noise could be removed without resolution degradation. Accordingly, flooded area could be distinguished effectively from other area in NL-means filtered image.