Abstract
In this paper we propose a method able to automatically detect good/bad colonies of iPS cells using local patches based on densely extracted SIFT features. Different options for local patch classification based on a kernelized novelty detector, a 2-class SVM and a local Bag-of-Features approach are considered. Experimental results on 33 images of iPS cell colonies have shown that excellent accuracy can be achieved by the proposed approach.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines and Other Kernel-Base Learning Methods. Cambridge University Press (2000)
Ebben, J.D., Zorniak, M., Clark, P.A., Kuo, J.S.: Introduction to induced pluripotent stem cells: Advancing the potential for personalized medicine. World Neurosurg. 76(3–4), 270–275 (2011)
Joutsijoki, H., et al.: Classification of ipsc colony images using hierarchical strategies with support vector machines. In: IEEE Symp. CIDM 2014, pp. 86–92 (2014)
Kazutoshi, T., Koji, T., Mari, O., Megumi, N., Tomoko, I., Kiichiro, T., Shinya, Y.: Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell 131(5), 861–871 (2007)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal Computer Vision 60(2), 91–110 (2004)
Tax, D., Duin, R.: Data domain description by support vectors. In: Proceedings of ESANN 1999, pp. 251–256 (1999)
Watanabe, H., Tanabe, K., Kii, H., Ishikawa, M., Nakada, C., Uozumi, T., Kiyota, Y., Wada, Y., Tsuchiya, R.: Establishment of an algorithm for automated detection of ips/non-ips cells under a culture condition by noninvasive image analysis (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Masuda, A. et al. (2015). Automatic Detection of Good/Bad Colonies of iPS Cells Using Local Features. In: Zhou, L., Wang, L., Wang, Q., Shi, Y. (eds) Machine Learning in Medical Imaging. MLMI 2015. Lecture Notes in Computer Science(), vol 9352. Springer, Cham. https://doi.org/10.1007/978-3-319-24888-2_19
Download citation
DOI: https://doi.org/10.1007/978-3-319-24888-2_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24887-5
Online ISBN: 978-3-319-24888-2
eBook Packages: Computer ScienceComputer Science (R0)