Microscopy Cell Counting and Annotation Using a Max-Tree Representation of the Blood Cell Images
Author:
Affiliation:
1. Department of CSE, University of Asia Pacific, Dhaka, Bangladesh
Publisher
ACM Press
Reference19 articles.
1. Arteta, C., Lempitsky, V. S., Noble, J. A., and Zisserman A. 2012. Learning to detect cells using non-overlapping extremal regions. MICCAI (1), volume 7510 of Lecture Notes in Computer Science, pages 348--356. Springer.
2. Arteta, C., Lempitsky, V. S., Noble, J. A., and Zisserman A. 2014. Interactive object counting. In David Fleet, Tomas Pajdla, Bernt Schiele, and Tinne Tuytelaars, editors, Computer Vision - ECCV 2014, pages 504--518, Cham. Springer International Publishing.
3. Belkacem-Boussaid, K., Sertel, O., Lozanski, G., Shana'aah, A., and Gurcan, M. 2009. Extraction of color features in the spectral domain to recognize centroblasts in histopathology. In Engineering in Medicine and Biology Society. EMBC 2009. Annual International Conference of the IEEE, pages 3685--3688.
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5. Cheng, J., Veronika, M. and Rajapakse, J. C. 2010. Identifying cells in histopathological images. In Devrim Ünay, Zehra Çataltepe, and Selim Aksoy, editors, Recognizing Patterns in Signals, Speech, Images and Videos, pages 244--252, Berlin, Heidelberg. Springer Berlin Heidelberg. ISBN 978-3-642-17711-8.
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