Abstract
We present an image analysis pipeline for identifying cells in histopathology images of cancer. The analysis starts with segmentation using multi-phase level sets, which is insensitive to initialization and enables automatic detection of arbitrary objects. Morphological operations are used to remove small spots in the segmented images. The target cells are then identified based on their features. The detected cells were compared with the manual detection performed by pathologists. The quantitative evaluation shows promise and utility of our technique.
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Cheng, J., Veronika, M., Rajapakse, J.C. (2010). Identifying Cells in Histopathological Images. In: Ünay, D., Çataltepe, Z., Aksoy, S. (eds) Recognizing Patterns in Signals, Speech, Images and Videos. ICPR 2010. Lecture Notes in Computer Science, vol 6388. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17711-8_25
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DOI: https://doi.org/10.1007/978-3-642-17711-8_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17710-1
Online ISBN: 978-3-642-17711-8
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