| Literature DB >> 23796718 |
André Homeyer1, Andrea Schenk, Janine Arlt, Uta Dahmen, Olaf Dirsch, Horst K Hahn.
Abstract
Since the histological quantification of necrosis is a common task in medical research and practice, we evaluate different image analysis methods for quantifying necrosis in whole-slide images. In a practical usage scenario, we assess the impact of different classification algorithms and feature sets on both accuracy and computation time. We show how a well-chosen combination of multiresolution features and an efficient postprocessing step enables the accurate quantification necrosis in gigapixel images in less than a minute. The results are general enough to be applied to other areas of histological image analysis as well.Entities:
Keywords: Histological image analysis; Necrosis quantification; Pattern recognition; Whole-slide imaging
Mesh:
Year: 2013 PMID: 23796718 DOI: 10.1016/j.compmedimag.2013.05.002
Source DB: PubMed Journal: Comput Med Imaging Graph ISSN: 0895-6111 Impact factor: 4.790