کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
378094 658878 2008 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A reliable method for cell phenotype image classification
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
A reliable method for cell phenotype image classification
چکیده انگلیسی

SummaryObjectiveImage-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 materialsIn this work, the invariant locally binary patterns (LBP) are applied, for the first time, to the classification of protein sub-cellular localization images. They are tested on three image datasets (available for download), in conjunction with support vector machines (SVMs) and random subspace ensembles of neural networks. Our method based on invariant LBP provides higher accuracy than other well-known methods for feature extraction; moreover, our method does not require to (direct) crop the cells for the classification.Results and conclusionThe experimental results show that the random subspace ensemble of neural networks outperforms the SVM in this problem. The proposed approach based on the solely LBP features gives accuracies of 85%, 93.9% and 88.4% on the 2D HeLa dataset, LOCATE endogenous and transfected datasets, respectively, and in combination with other state-of-the-art methods for the cell phenotype image classification we obtain a classification accuracy of 94.2%, 98.4% and 96.5%.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Artificial Intelligence in Medicine - Volume 43, Issue 2, June 2008, Pages 87–97
نویسندگان
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