Fast automated cell phenotype image classification
نویسندگان
چکیده
منابع مشابه
Ensemble of Neural Networks for Automated Cell Phenotype Image Classification
Subcellular location is related to the knowledge of the spatial distribution of a protein within the cell. The knowledge of the location of all proteins is crucial for several applications ranging from early diagnosis of a disease to monitoring of therapeutic effectiveness of drugs. This chapter focuses on the study of machine learning techniques for cell phenotype image classification and is a...
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In this paper our aim is to study how an ensemble of classifiers can improve the performance of a machine learning technique for cell phenotype image classification. We want to point out some of the advantages that an ensemble of classifiers permits to obtain respect a stand-alone method. Finally, the preliminary results on the 2D-HeLa dataset, obtained by the fusion between a random subspace o...
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OBJECTIVE Image-based approaches have proven to be of great utility in the automated cell phenotype classification, it is very important to develop a method that efficiently quantifies, distinguishes and classifies sub-cellular images. METHODS AND MATERIALS In this work, the invariant locally binary patterns (LBP) are applied, for the first time, to the classification of protein sub-cellular ...
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ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2007
ISSN: 1471-2105
DOI: 10.1186/1471-2105-8-110