title: [Neighborhood graphs and image processing. Contribution to images of immunohistochemical staining].
abstract: Devising an image analyzer dedicated to the automatic quantification of immunohistochemical staining for clinical oncology implies developing a method for the delimitation of tumoral cell nests, setting aside tumoral stroma, while accounting for the topology of the staining. The representation of images by neighborhood graphs can bring an answer to both requirements. In this paper, a methodological approach is presented. It consists in a preliminary study dealing with nuclear immunostaining images of breast cancer. Segmentation of the graph structure allows to separate clusters of cancer cells and the analysis of this structure can account for the focal or diffuse aspect of the staining within the tumor.
authors.affiliation: Laboratoire Greyc-Upresa CNRS 6072-ISMRA, Caen, France.
authors.forename: F
authors.initials: F
authors.lastname: Angot
authors.forename: P
authors.initials: P
authors.lastname: Herlin
authors.forename: A
authors.initials: A
authors.lastname: Elmoataz
authors.forename: M
authors.initials: M
authors.lastname: Revenu
authors.forename: A M
authors.initials: AM
authors.lastname: Mandard
authors.forename: D
authors.initials: D
authors.lastname: Bloyet
mesh_terms: D001943:Breast Neoplasms / Q000473:pathology*; D002467:Cell Nucleus; D003196:Computer Graphics; D004848:Epithelium / Q000473:pathology; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007150:Immunohistochemistry / Q000379:methods; D013194:Staining and Labeling / Q000379:methods; D017154:Stromal Cells / Q000473:pathology