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Identifying Neutrophils in H&E Staining Histology Tissue Images

  • Jiazhuo Wang
  • John D. MacKenzie
  • Rageshree Ramachandran
  • Danny Z. Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8673)

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.

Keywords

Segmentation Result Voronoi Diagram Hard Case Probability Output Training Region 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jiazhuo Wang
    • 1
  • John D. MacKenzie
    • 2
  • Rageshree Ramachandran
    • 3
  • Danny Z. Chen
    • 1
  1. 1.Department of Computer Science & EngineeringUniversity of Notre DameUSA
  2. 2.Department of Radiology & Biomedical ImagingUCSFUSA
  3. 3.Department of Pathology & Laboratory MedicineUCSFUSA

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