RECOGNIZE AND CLASSIFY FISH OOCYTES IN HISTOLOGICAL IMAGES

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原文链接

NETL

外文摘要：The study of biology and population dynamics of fish species requires the estimation of fecundity in individual fish in many fisheries laboratories。 The traditional procedure used by fisheries research is to count manually the oocytes on a subsample of known weight of the ovary， and to measure a few oocytes under a binocular microscope。 This process can 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。We attempt to design a computer vision system which is able to recognize and classify the oocytes in a histolog-ical image。 The boundary of oocytes is detected using an algorithm based on edge information。 Afterwards， oocytes are classified in cells with and without nucleus。 A statistical evaluation of both stages reveals correct detection and classification of 65% when a 80% of overlap is demanded。

外文关键词：

image analysisclassificationsegmentationfish oocytesfecundityhistological images

作者：

E. Cernadas、P. Carrion、A. Formella、R. Dominguez、F. Saborido-Rey

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作者单位：

Dpto. de Electronica e Computation Campus Sur s/n 15782 Santiago de Compostela A Coruna (Spain)

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

Instituto de Investigations Marinas CSIC, Vigo (Spain)

会议名称：

IASTED international conference on visualization, imaging, and image processing;VIIP 2008

会议地点：

Palma de Mallorca(ES);Palma de Mallorca(ES)

会议母体文献：

Visualization, imaging, and image processing

页码：

180-186

出版时间：

2008