Consulta: subjectFacets:"Analyse d'image"
Registros recuperados: 7
Data/hora: 01/06/2024 09:48:58

Version évolutive de l’outil opérationnel de numérisation et d’analyse semi-automatique d’images de phytoplancton, utilisant le matériel FlowCAM et le logiciel ZooPhytoImage. Nouvelles perspectives
Provedor de dados: 5
Autores: Wacquet, Guillaume; Grosjean, Philippe; Colas, Florent; Hamad, Denis; Artigas, Luis Felipe.
The coupled system FlowCAM/ZooPhytoImage has become a real operational tool in 2014. However, to be fully adapted to the observations of phytoplankton performed in the context of the REPHY observation network and in order to better respond to present and future requests concerning the evaluation of quality of coastal and marine waters within the European requirements, such as the WFD and MSFD, new functionalities must be integrated into existing tools. Therefore, different axis of development have been proposed by UMONS and Ifremer to adapt both the digitization device and the Zoo/PhytoImage software to the constraints defined by the REPHY. First, version 5 of Zoo/PhytoImage contains recent innovations such as the development of routines to automatically...
Tipo: Text
Palavras-chave: Plancton; Analyse automatisée; Analyse d'image; Classification supervisée; Apprentissage actif; Dénombrement de cellules; Plankton; Automated analysis; Image processing; Supervised classification; Active learning; Cells counting.
Ano: 2015
URL: http://archimer.ifremer.fr/doc/00389/49986/50573.pdf

Application of a digital pattern recognition system to Dinophysis acuminata and D-sacculus complexes
Provedor de dados: 5
Autores: Truquet, Philippe; Lassus, Patrick; Honsell, Giorgio; Le Dean, Loic.
An image discrimination technique was developed to improve specific identification of some toxic Dinophysis cells (marine dinoflagellates involved in diarrhoeic shellfish poisoning), especially the ''acuminata'' and ''sacculus'' groups, which can be present at different ratios in natural sea-water samples collected during toxic episodes. This work was performed with image analysis software SAMBA (TITN Alcatel) using preserved cells directly observed through an inverted microscope and recorded with a video camera before further processing. All morphometric parameters used for discrimination of 7 different species or morphotypes of Dinophysis were tested with discriminant analysis. This study indicates that Dinophysis sp. and D. pavillardi seem well...
Tipo: Text
Palavras-chave: Dinophysis sp.; Analyse d'image; Taxonomie; Phytoplancton; Dinophysis sp; Image analysis; Taxonomy; Phytoplankton.
Ano: 1996
URL: http://archimer.ifremer.fr/doc/00188/29890/28337.pdf

Utilisation conjointe de FlowCAM / ZooPhytoImage et de la cytométrie en flux. Premiers résultats et perspectives. Action 9. FlowCam ZooPhytoImage. Livrable n° 4. Rapport final, 23 septembre 2014
Provedor de dados: 5
Autores: Ali, Nour; Wacquet, Guillaume; Didry, Morgane; Hamad, Denis; Artigas, Luis Felipe; Grosjean, Philippe.
The goal of this study is to investigate about the possibility of coupling measurements made by image analysis from the FlowCAM with Zoo/PhytoImage with data obtained with a flux cytometer (pulse-shape-recording Scanning Flow Cytometry) on the same samples gathered in current monitoring networks in the eastern Channel and southern North Sea. In this preliminary study, we collected a series of samples off Boulogne-sur-Mer (SRN-REPHY monitoring system run by IFREMER) and along a transect in the Baie St-Jean (Wimereux-Slack) run by LOG. All these samples were digitized with a FlowCAM and measured with a scanning flow cytometer (CytoSense). The complete analysis with the FlowCAM and Zoo/PhytoImage is detailed in the present report. In order to get a better...
Tipo: Text
Palavras-chave: Manche – Mer du Nord; Phytoplancton; Analyse d'image; Classification supervisée; Cytométrie en flux; Eastern English Channel and southern North Sea; Phytoplankton; Image analysis; Machine learning; Scanning Flow Cytometry.
Ano: 2014
URL: http://archimer.ifremer.fr/doc/00363/47442/47470.pdf

Caractérisation de types hémocytaires dans l'hémolymphe de l'huître plate, Ostrea edulis, par classification robuste
Provedor de dados: 5
Autores: Segretin, Angelique.
Les méthodes de classification sont largement utilisées en vision par ordinateur et reconnaissance des formes. La classification floue a d'ailleurs montré de bonnes performances dans ces domaines, non seulement dans la reconnaissance de classes en volume, mais aussi pour des formes fines, des droites, des courbes, et également des surfaces. L'idée est d'utiliser la classification automatique pour tenter de caractériser des types hémocytaires présents dans l'hémolymphe de l'huître plate. Actuellement, trois types d'hémocyte ont été définis, mais la difficulté d'établir un classement des cellules dans ces trois groupes, laisse penser qu'ils ne sont pas exhaustifs. Différentes approches de classification ont été tentées sur des mesures morphométriques de...
Tipo: Text
Palavras-chave: Classification floue; Analyse d'image; Huître plate; Ostrea edulis; Hémocytes.
Ano: 1997
URL: http://archimer.ifremer.fr/doc/00033/14445/11744.pdf

Induction de la triploïdie chez l'huître creuse Crassostrea gigas par rétention du premier ou du second globule polaire
Provedor de dados: 5
Autores: Roux, Isabelle.
La gonadogenèse chez les mollusques bivalves mobilise le métabolisme énergétique de l'animal, engendre un ralentissement de la croissance et une mortalité accrue des animaux fragilisés. La triploïdisation, qui consiste en une augmentation artificielle du matériel chromosomique d'un individu, aboutit à une stérilité partielle, voire totale, et constituerait ainsi une solution aux problèmes posés par la maturation sexuelle. , Chez l'huître creuse Crassostrea g!gas, l'obtention de lots triploïdes 3N-Méiose 1 et 3N-Méiose II "bien différenciés est considérablement gênée par le manque de synchronisme existant chez une population d'embryons pour l'expulsion des deux GP. Cette absence de synchronisme empêche de bien cerner le moment idéal d'application du...
Tipo: Text
Palavras-chave: Triploïdisation; Globules plaires 1 et 2; 6-DMAP; Epifluorescence; Analyse d'image.
Ano: 1993
URL: http://archimer.ifremer.fr/doc/00411/52222/52949.pdf

Guide méthodologique. Version actualisée de ZooPhytoImage avec refonte de l’interface graphique. Action 9. FlowCam ZooPhytoImage. Livrable n°1. Rapport final
Provedor de dados: 5
Autores: Grosjean, Philippe.
Zoo/PhytoImage 4 is an « open source » software based on R and ImageJ. It processes numerical images of plankton particles digitized using a FlowCAM, a flat-bed scanner, microor macrophotos, etc. The general concept consists in the individual outlining of particles on the pictures, followed by their measurements (so-called « attributes ») such the size, the shape, transparency, textures, etc. These attributes are then used by a classification tool to automatically predict the taxonomic group the particles belong to. The classifier is obtained after a learning stage using a machine learning algorithm and a training set of pre-identified particles. The algorithm learns to recognize the taxonomic group from the set of attributes measured on the picture. The...
Tipo: Text
Palavras-chave: Océanographie biologique; Plancton; Surveillance côtière; Analyse automatisée; Analyse d'image; Classification supervisée; Biological oceanography; Plankton; Costal survey; Automated analysis; Image analysis; Machine learning.
Ano: 2014
URL: http://archimer.ifremer.fr/doc/00363/47436/47461.pdf

Optimisation de l’identification et du dénombrement du microphytoplancton avec le système couplé de numérisation et d’analyse d’images FlowCAM – Zoo/PhytoImage (système innovant)
Provedor de dados: 5
Autores: Grosjean, Philippe; Wacquet, Guillaume.
This report details the work accomplished to enhance the Zoo/PhytoImage software to optimize its use for the analysis of phytoplankton samples in general, but more particularly, in the framework of an operational survey of coastal seawater (REPHY, IFREMER). Zoo/PhytoImage allows to analyze “numerically recorded” plankton samples, that is, by using digital images gathered with specialized devices such as the FlowCAM, or the FastCAM (see report 3). A machine learning approach allows to automatically classify the digitized particles into various taxonomic groups. Once this is done, global statistics are calculated on each sample, including the number of particles, the biomass, and the size spectrum per taxonomic group. Two major changes are introduced in the...
Tipo: Text
Palavras-chave: Phytoplancton; REPHY; Analyse d'image; Classification supervisée; Dénombrement de cellules; Apprentissage actif; Manche; Atlantique.; Phytoplankton; REPHY; Image analysis; Machine learning; Cells enumeration; Active learning; The Channel; Atlantic Ocean.
Ano: 2016
URL: http://archimer.ifremer.fr/doc/00389/49990/50578.pdf