| Literature DB >> 25475487 |
Philippe Belhomme1, Simon Toralba2, Benoît Plancoulaine3, Myriam Oger4, Metin N Gurcan5, Catherine Bor-Angelier4.
Abstract
Computerized image analysis (IA) can provide quantitative and repeatable object measurements by means of methods such as segmentation, indexation, classification, etc. Embedded in reliable automated systems, IA could help pathologists in their daily work and thus contribute to more accurate determination of prognostic histological factors on whole slide images. One of the key concept pathologists want to dispose of now is a numerical estimation of heterogeneity. In this study, the objective is to propose a general framework based on the diffusion maps technique for measuring tissue heterogeneity in whole slide images and to apply this methodology on breast cancer histopathology digital images.Entities:
Keywords: Breast cancer; Dimensionality reduction; Heterogeneity; Spectral graph theory; Whole slide image
Mesh:
Year: 2014 PMID: 25475487 DOI: 10.1016/j.compmedimag.2014.11.006
Source DB: PubMed Journal: Comput Med Imaging Graph ISSN: 0895-6111 Impact factor: 4.790