Format

Send to

Choose Destination
IEEE Rev Biomed Eng. 2016;9:234-63. doi: 10.1109/RBME.2016.2515127. Epub 2016 Jan 6.

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

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 recent state-of-the-art nucleus/cell segmentation approaches on different types of microscopy images including bright-field, phase-contrast, differential interference contrast, fluorescence, and electron microscopies. In addition, we discuss the challenges for the current methods and the potential future work of nucleus/cell detection and segmentation.

PMID:
26742143
PMCID:
PMC5233461
DOI:
10.1109/RBME.2016.2515127
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for IEEE Engineering in Medicine and Biology Society Icon for PubMed Central
Loading ...
Support Center