Please use this identifier to cite or link to this item:
|標題:||A protozoan parasite extraction scheme for digital microscopic images||作者:||Lai, C.H.
|關鍵字:||Protozoan parasites;Microscopic images;Cell extraction scheme;Gamma;equalization;Two-means clustering;edge enhancement;children||Project:||Computerized Medical Imaging and Graphics||期刊/報告no：:||Computerized Medical Imaging and Graphics, Volume 34, Issue 2, Page(s) 122-130.||摘要:||
Pathogenic protozoan parasites can cause human to get many diseases, such as, amoebiasis, typhoid fever and cholera, etc. Different protozoan parasites vary greatly in their structural and biochemical properties. Digital images are extensively applied to medical fields for doctors and pathologists to analyze pathological sections and further diagnose diseases. The aim of this paper is to develop protozoan parasite extraction techniques to segment protozoan parasites from microscopic images. The proposed scheme has precise segmentation ability even if the image is with poor quality or complex background. Experimental results show that the proposed scheme can gain 96.64% average correct rate, and about 0.04, 0.45 and 0.06 of the average error rates: misclassification error (ME), region non-uniformity (RN) and relative foreground area error (RFAE), respectively. (C) 2009 Elsevier Ltd. All rights reserved.
|Appears in Collections:||資訊科學與工程學系所|
Show full item record
TAIR Related Article
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.