Semi-automated recognition of protozoa by image analysis

被引：20

作者：

Amaral, AL

Baptiste, C

Pons, MN

Nicolau, A

Lima, N

Ferreira, EC

Mota, M ^{[1
]}

Vivier, H

机构：

[1] Univ Minho, IBQF, Ctr Engn Biol, P-4700 Braga, Portugal

[2] ENSIC, Lab Sci Genie Chim, Nancy, France

来源：

BIOTECHNOLOGY TECHNIQUES | 1999年 / 13卷 / 02期

关键词：

protozoa; image analysis; wastewater treatment; principal component analysis;

D O I：

10.1023/A:1008850701796

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

A programme was created to semi-automatically analyse protozoal digitised images. Principal Component Analysis technique was used for species identification. After data collection and mathematical treatment, a three-dimensional representation was generated and several protozoa (Opercularia, Colpidium, Tetrahymena, Prorodon, Glaucoma and Trachelophyllum) species could be positively identified.

引用

页码：111 / 118

页数：8

共 20 条

[1] The use of principal component analysis as a database mining tool for the exploratory diagnosis of chromatographic processes [J].