Novel cell segmentation and online SVM for cell cycle phase identification in automated microscopy
Open Access
- 7 November 2007
- journal article
- research article
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 24 (1), 94-101
- https://doi.org/10.1093/bioinformatics/btm530
Abstract
Motivation: Automated identification of cell cycle phases captured via fluorescent microscopy is very important for understanding cell cycle and for drug discovery. In this article, we propose a novel cell detection method that utilizes both the intensity and shape information of the cell for better segmentation quality. In contrast to conventional off-line learning algorithms, an Online Support Vector Classifier (OSVC) is thus proposed, which removes support vectors from the old model and assigns new training examples weighted according to their importance to accommodate the ever-changing experimental conditions. Results: We image three cell lines using fluorescent microscopy under different experiment conditions, including one treated with taxol. Then, we segment and classify the cell types into interphase, prophase, metaphase and anaphase. Experimental results show the effectiveness of the proposed system in image segmentation and cell phase identification. Availability: The software and test datasets are available from the authors. Contact:zhou@crystal.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online.Keywords
This publication has 32 references indexed in Scilit:
- A Support Vector Machine Classifier for Recognizing Mitotic Subphases Using High-Content Screening DataSLAS Discovery, 2007
- Efficient optimization of support vector machine learning parameters for unbalanced datasetsJournal of Computational and Applied Mathematics, 2006
- Automated Segmentation, Classification, and Tracking of Cancer Cell Nuclei in Time-Lapse MicroscopyIEEE Transactions on Biomedical Engineering, 2006
- In vitro modelling of human tumour behaviour in drug discovery programmesEuropean Journal of Cancer, 2004
- Image analysis for automatic segmentation of cytoplasms and classification of Rac1 activationCytometry Part A, 2003
- Online training of support vector classifierPattern Recognition, 2003
- Therapeutic Exploitation of Checkpoint Defects in Cancer Cells Lacking p53 FunctionCell Cycle, 2002
- Texture features for browsing and retrieval of image dataIeee Transactions On Pattern Analysis and Machine Intelligence, 1996
- Support-vector networksMachine Learning, 1995
- The perceptron: A probabilistic model for information storage and organization in the brain.Psychological Review, 1958