1.Two cases of congenital hepatic fibrosis.
Cue Jung HWANG ; Young Hun KIM ; Dae Kyun KOH ; Byung Churl LEE
Journal of the Korean Pediatric Society 1992;35(4):569-574
No abstract available.
Fibrosis*
2.Renal Fibrosis and Transforming Growth Factor-beta1.
Journal of the Korean Pediatric Society 2001;44(3):285-291
No abstract available.
Fibrosis*
3.Pharmacologic Therapy of Hepatic Fibrosis.
The Korean Journal of Hepatology 2001;7(1):6-11
No abstract availalbe.
Fibrosis*
4.A Case of Congenital Hepatic Fibrosis with Hypersplenism.
Hye Suk HONG ; Yang Won LEE ; Keon su RHEE ; Young Hun CHUNG
Journal of the Korean Pediatric Society 1987;30(12):1456-1460
No abstract available.
Fibrosis*
;
Hypersplenism*
5.A Case of Retroperitoneal Fibrosis Treated with Longitudinal Ureteromyotomy Successfully.
Jun Mo KIM ; Young Ho KIM ; Yoon Soon JEON ; Nam Kyu LEE
Korean Journal of Urology 2000;41(9):1151-1153
No abstract available.
Retroperitoneal Fibrosis*
6.A Case of Retroperitoneal Fibrosis with Regression by Steroid Therapy.
Seung Yeup HAN ; Choong Hwan KWAK ; Hyun Chul KIM ; Chun Il KIM
Korean Journal of Medicine 2005;68(6):717-718
No abstract available.
Retroperitoneal Fibrosis*
7.Image Standardization and Determination of Gray Level Threshold in the Assessment of the Myocardial Fibrosis by the Computerized Image Analysis.
Nam Young LEE ; Young Sik PARK ; Jin Haeng CHUNG ; Jeong Wook SEO
Korean Journal of Pathology 1998;32(7):494-503
The computerized image analysis is a useful tool for the quantitative assessment of histopathologic findings. In contrast to the usual microscopic examination by pathologists, the computerization should be accompanied with the standardization process of the image. We developed an algorithm to standardize images and to determine the optimal gray level threshold, using a myocardial fibrosis model. Sirius red staining was more convenient for the image analysis than Masson's trichrome staining because of a better contrast with the surrounding structures. To get an optimal measurement, light intensity was standardized at each of the fibrosis, myocardium and background. In this study, the most promising method to determine the degree of fibrosis was that of revising the background without tissue to a gray level of 200, obtaining a green component of the color image, revising the myocardial fiber to 163, and defining a partial ratio as fibrosis index when the gray level threshold was 120. These threshold levels and parameters were determined after drawing the binarization index curves according to the change of the gray level threshold and by the morphological examination of the actual binarization figures overlaid to the original color image. Through these processes we could get a consistent result on the myocardial fibrosis and we expect a similar principle applies when we analyze color images in the histopathologic quantitation by computerized image analysis.
Fibrosis*
;
Myocardium
9.Another Face of Contrast-Enhanced Ultrasonography: A Diagnostic Tool for Cirrhosis.
Gut and Liver 2017;11(1):9-10
No abstract available.
Fibrosis*
;
Ultrasonography*
10.Tseatment of Idioparhic Pulmonary Fibrosis.
Tuberculosis and Respiratory Diseases 2003;54(3):260-273
No abstract available.
Pulmonary Fibrosis*
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