Abstract
Identifying neutrophils lays a crucial foundation for diagnosing acute inflammation diseases. But, such computerized methods on the commonly used H&E staining histology tissue images are lacking, due to various inherent difficulties of identifying cells in such image modality and the challenge that a considerable portion of neutrophils do not have a “textbook” appearance. In this paper, we propose a new method for identifying neutrophils in H&E staining histology tissue images. We first segment the cells by applying iterative edge labeling, and then identify neutrophils based on the segmentation results by considering the “context” of each candidate cell constructed by a new Voronoi diagram of clusters of other neutrophils. We obtain good performance compared with two baseline algorithms we constructed, on clinical images collected from patients suspected of having inflammatory bowl diseases.
This research was supported in part by NSF Grant CCF-1217906, a grant of the National Academies Keck Futures Initiative (NAKFI), and NIH grant K08-AR061412-02 Molecular Imaging for Detection and Treatment Monitoring of Arthritis.
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Wang, J., MacKenzie, J.D., Ramachandran, R., Chen, D.Z. (2014). Identifying Neutrophils in H&E Staining Histology Tissue Images. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014. MICCAI 2014. Lecture Notes in Computer Science, vol 8673. Springer, Cham. https://doi.org/10.1007/978-3-319-10404-1_10
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DOI: https://doi.org/10.1007/978-3-319-10404-1_10
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