Please use this identifier to cite or link to this item:
|標題:||AN ITERATIVE BASED NOVEL MULTI-NUCLEUS DETECTION SCHEME FOR PROTOZOAN PARASITE MICROSCOPIC IMAGES||作者:||Lai, C.H.
|關鍵字:||Protozoan parasites;Microscope images;Nucleus detection;Gamma;equalization;Boundary erasure;Connected component;Circular masks;segmentation;children;regions||Project:||International Journal of Innovative Computing Information and Control||期刊/報告no：:||International Journal of Innovative Computing Information and Control, Volume 5, Issue 11A, Page(s) 3875-3886.||摘要:||
Protozoan parasites cause many diseases, such as malaria, EHEC infection, shigellosis, amoebiasis, etc. Different kinds and growing stages of protozoan parasites would lead to different treatments. The most significant characteristic of different growing stages is the number of nuclei. But some nuclei in a cell could be unclear causing the missing in nucleus detection. Common and traditional segmentation methods can not be used to obtain satisfied results directly. This paper presents a novel multi-nucleus detection scheme which is composed from adaptive protozoan parasite boundary erasure, iterative gamma equalization, two-means clustering algorithm, modified connected component detection method, and circle mask scoring method. Except the two-means clustering algorithm, all other parts are modified methods or new methods designed for nucleus extraction, Experiments show that the proposed scheme can detect the nuclei with indistinct boundaries effectively and can obtain better results than other commonly used image segmentation methods.
|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.