Matches in SemOpenAlex for { <https://semopenalex.org/work/W2074809724> ?p ?o ?g. }
Showing items 1 to 88 of
88
with 100 items per page.
- W2074809724 abstract "In biological studies, Saccharomyces cerevisiae yeast cells are used to study the behaviour of proteins. This is a time consuming and not completely objective process. Hence, image analysis platforms are developed to address these problems and to offer analysis per cell as well. The segmentation algorithms implemented in such platforms can segment the healthy cells, along with artefacts such as debris and dead cells that exist in the cultured medium. The novel idea in this work is to apply a machine learning approach to train the segmentation system in order to classify the healthy cell objects from the other objects. Such approach is based on the analysis of a set of relevant individual cell features extracted from the microscope images of yeast cells. These features include texture measurements and wavelet-based texture measurements, as well as moment invariant features. Those features were introduced to describe the intensity and morphology characteristics in a more sophisticated way. A set of classification systems, data sampling techniques, data normalization schemes and feature selection algorithms were tested and evaluated to build a classification model in order to be used within the segmentation module. The study picks the simple logistic classification model as the best approach to classify our dataset of 1380 cells. This system increases the performance level in our image and data analysis modules, improve the segmentation and consequently the analysis of the measurement results. This leads to a better pattern recognition system as well." @default.
- W2074809724 created "2016-06-24" @default.
- W2074809724 creator A5022631255 @default.
- W2074809724 creator A5084357849 @default.
- W2074809724 date "2015-09-01" @default.
- W2074809724 modified "2023-09-24" @default.
- W2074809724 title "Machine learning approach to segment Saccharomyces cerevisiae yeast cells" @default.
- W2074809724 cites W1637045490 @default.
- W2074809724 cites W1845661282 @default.
- W2074809724 cites W1966372021 @default.
- W2074809724 cites W1966705856 @default.
- W2074809724 cites W1969197825 @default.
- W2074809724 cites W1979888186 @default.
- W2074809724 cites W2059432853 @default.
- W2074809724 cites W2108164443 @default.
- W2074809724 cites W2117395697 @default.
- W2074809724 cites W2129526018 @default.
- W2074809724 cites W2133990480 @default.
- W2074809724 cites W2154830650 @default.
- W2074809724 cites W2158698691 @default.
- W2074809724 cites W2159498975 @default.
- W2074809724 cites W2330470541 @default.
- W2074809724 cites W2585266934 @default.
- W2074809724 cites W3147935524 @default.
- W2074809724 doi "https://doi.org/10.1109/icabme.2015.7323306" @default.
- W2074809724 hasPublicationYear "2015" @default.
- W2074809724 type Work @default.
- W2074809724 sameAs 2074809724 @default.
- W2074809724 citedByCount "1" @default.
- W2074809724 countsByYear W20748097242021 @default.
- W2074809724 crossrefType "proceedings-article" @default.
- W2074809724 hasAuthorship W2074809724A5022631255 @default.
- W2074809724 hasAuthorship W2074809724A5084357849 @default.
- W2074809724 hasConcept C124101348 @default.
- W2074809724 hasConcept C124504099 @default.
- W2074809724 hasConcept C136886441 @default.
- W2074809724 hasConcept C144024400 @default.
- W2074809724 hasConcept C148483581 @default.
- W2074809724 hasConcept C153180895 @default.
- W2074809724 hasConcept C154945302 @default.
- W2074809724 hasConcept C19165224 @default.
- W2074809724 hasConcept C2777576037 @default.
- W2074809724 hasConcept C2779222958 @default.
- W2074809724 hasConcept C41008148 @default.
- W2074809724 hasConcept C54355233 @default.
- W2074809724 hasConcept C86803240 @default.
- W2074809724 hasConcept C89600930 @default.
- W2074809724 hasConceptScore W2074809724C124101348 @default.
- W2074809724 hasConceptScore W2074809724C124504099 @default.
- W2074809724 hasConceptScore W2074809724C136886441 @default.
- W2074809724 hasConceptScore W2074809724C144024400 @default.
- W2074809724 hasConceptScore W2074809724C148483581 @default.
- W2074809724 hasConceptScore W2074809724C153180895 @default.
- W2074809724 hasConceptScore W2074809724C154945302 @default.
- W2074809724 hasConceptScore W2074809724C19165224 @default.
- W2074809724 hasConceptScore W2074809724C2777576037 @default.
- W2074809724 hasConceptScore W2074809724C2779222958 @default.
- W2074809724 hasConceptScore W2074809724C41008148 @default.
- W2074809724 hasConceptScore W2074809724C54355233 @default.
- W2074809724 hasConceptScore W2074809724C86803240 @default.
- W2074809724 hasConceptScore W2074809724C89600930 @default.
- W2074809724 hasLocation W20748097241 @default.
- W2074809724 hasOpenAccess W2074809724 @default.
- W2074809724 hasPrimaryLocation W20748097241 @default.
- W2074809724 hasRelatedWork W1969543216 @default.
- W2074809724 hasRelatedWork W1975580656 @default.
- W2074809724 hasRelatedWork W2040965063 @default.
- W2074809724 hasRelatedWork W2045844866 @default.
- W2074809724 hasRelatedWork W2078504607 @default.
- W2074809724 hasRelatedWork W2105790678 @default.
- W2074809724 hasRelatedWork W2135523248 @default.
- W2074809724 hasRelatedWork W2147219845 @default.
- W2074809724 hasRelatedWork W2148391495 @default.
- W2074809724 hasRelatedWork W2152768474 @default.
- W2074809724 hasRelatedWork W2165771856 @default.
- W2074809724 hasRelatedWork W2169357235 @default.
- W2074809724 hasRelatedWork W2203777347 @default.
- W2074809724 hasRelatedWork W2540692237 @default.
- W2074809724 hasRelatedWork W2766066477 @default.
- W2074809724 hasRelatedWork W2783449176 @default.
- W2074809724 hasRelatedWork W2950934157 @default.
- W2074809724 hasRelatedWork W3109168350 @default.
- W2074809724 hasRelatedWork W944921222 @default.
- W2074809724 hasRelatedWork W2191593557 @default.
- W2074809724 isParatext "false" @default.
- W2074809724 isRetracted "false" @default.
- W2074809724 magId "2074809724" @default.
- W2074809724 workType "article" @default.