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Enuresis as a Presenting Symptom of Graves' Disease: A Case Report
Hwang, Inseong,Park, Eujin,Lee, Hye Jin Korean Society of Pediatric Nephrology 2021 Childhood kidney diseases Vol.25 No.1
Enuresis is intermittent urinary incontinence during sleep at night in children aged 5 years or older. The main pathophysiology of enuresis involves nocturnal polyuria, abnormal sleep arousal, and low functional bladder capacity. In rare cases, enuresis is an early symptom of endocrine disorders such as diabetes or thyroid disorders. Herein, we report a case of a 12-year-old girl with enuresis as a rare initial presentation of Graves' disease. She complained of nocturnal enuresis from a month before visiting our clinic. She also complained of urinary frequency, headache, and weight loss. On physical examination, she had tachycardia, intention tremors, and a diffuse goiter on her anterior neck with bruit on auscultation. Her thyroid function test results revealed hyperthyroidism, and Graves' disease was diagnosed as the thyroid stimulating hormone receptor autoantibody was positive. After treatment for Graves' disease with methimazole, symptoms of enuresis resolved within 2 weeks as she became clinically and biochemically euthyroid. In children with secondary enuresis, Graves' disease should be considered as a differential diagnosis, and signs of hyperthyroidism should be checked for carefully.
의류 검색용 회전 및 스케일 불변 이미지 분류 및 검색 기술
황인성(Inseong Hwang),조법근(Beobkeun Cho),전승우(Seungwoo Jeon),최윤식(Yunsik Choe) 한국방송·미디어공학회 2014 방송공학회논문지 Vol.19 No.3
The field of searching clothing, which is very difficult due to the nature of the informal sector, has been in an effort to reduce the recognition error and computational complexity. However, there is no concrete examples of the whole progress of learning and recognizing for cloth, and the related technologies are still showing many limitations. In this paper, the whole process including identifying both the person and cloth in an image and analyzing both its color and texture pattern is specifically shown for classification. Especially, deformable search descriptor, LBPROT_35 is proposed for identifying the pattern of clothing. The proposed method is scale and rotation invariant, so we can obtain even higher detection rate even though the scale and angle of the image changes. In addition, the color classifier with the color space quantization is proposed not to loose color similarity. In simulation, we build database by training a total of 810 images from the clothing images on the internet, and test some of them. As a result, the proposed method shows a good performance as it has 94.4% matching rate while the former Dense-SIFT method has 63.9%.