Comparison of Region and Edge Segmentation Approaches to Recognize Fish Oocytes in Histological Images

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NETL

外文摘要：The study of biology and population dynamics of fish species requires the estimation of fecundity in individual fish in a routine way in many fisheries laboratories。 The traditional procedure used by fisheries research is to count the oocytes manually on a subsample of known weight of the ovary， and to measure few oocytes under a binocular microscope。 This process could be done on a computer using an interactive tool to count and measure oocytes。 In both cases， the task is very time consuming， which implies that fecundity studies are rarely conducted routinely。 This work represents the first attempt to design an automatic algorithm to recognize the oocytes in histological images。 Two approaches based on region and edge information are described to segment the image and extract the oocytes。 An statistical analysis reveals that higher than 74% of oocytes are recognized for both approaches， when an overlapping area between machine detection and true oocyte demanded is greater than 75%。

外文关键词：

image analysissegmentationfish oocytesfecundityhistological images

作者：

S. Alen、E. Cernadas、A. Formella、R. Dommguez、F. Saborido-Rey

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作者单位：

Dpto de Informatica, E.S.E.I., Universidade de Vigo Campus Universitario As Lagoas s/n, 32004 Ourense, Spain

会议名称：

International Conference on Image Analysis and Recognition(ICIAR 2006) pt.2

会议地点：

Povoa de Varzim(PT)

会议母体文献：

Image Analysis and Recognition pt.2; Lecture Notes in Computer Science; 4142

页码：

853-864

出版时间：

2006