title: Identifying neutrophils in H&E staining histology tissue images.
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.
authors.forename: Jiazhuo
authors.initials: J
authors.lastname: Wang
authors.forename: John D
authors.initials: JD
authors.lastname: MacKenzie
authors.forename: Rageshree
authors.initials: R
authors.lastname: Ramachandran
authors.forename: Danny Z
authors.initials: DZ
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D002478:Cells, Cultured; D004396:Coloring Agents; D004801:Eosine Yellowish-(YS); D006416:Hematoxylin; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D015212:Inflammatory Bowel Diseases / Q000473:pathology*; D008853:Microscopy / Q000379:methods*; D009504:Neutrophils / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013194:Staining and Labeling
chemical_list: D004396:Coloring Agents; D004801:Eosine Yellowish-(YS); D006416:Hematoxylin