reviewIEEE Reviews in Biomedical EngineeringJan 1, 2016GREEN OA

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review

University of Florida

PubMed
Indexed incrossrefpubmed

Abstract

Digital pathology and microscopy image analysis is widely used for comprehensive studies of cell morphology or tissue structure. Manual assessment is labor intensive and prone to interobserver variations. Computer-aided methods, which can significantly improve the objectivity and reproducibility, have attracted a great deal of interest in recent literature. Among the pipeline of building a computer-aided diagnosis system, nucleus or cell detection and segmentation play a very important role to describe the molecular morphological information. In the past few decades, many efforts have been devoted to automated nucleus/cell detection and segmentation. In this review, we provide a comprehensive summary of the…

Citation impact

516
total citations
FWCI
82.11
Percentile
100%
References
357
Citations per year

Authors

2

Topics & keywords

Keywords
  • Segmentation
  • Computer science
  • Image segmentation
  • Artificial intelligence
  • Nucleus
  • Differential interference contrast microscopy
  • Microscopy
  • Digital image analysis
UN Sustainable Development Goals
  • Decent work and economic growth
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