Review
. 2016 Jan; 9:234-63.
doi: 10.1109/RBME.2016.2515127.

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

Fuyong Xing  Lin Yang  
  • PMID: 26742143
  •     180 References
  •     69 citations

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.

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IEEE Trans Med Imaging, 2013 Aug 06; 32(12). PMID: 23912498
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Automatic Cell Detection in Bright-Field Microscope Images Using SIFT, Random Forests, and Hierarchical Clustering.
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IEEE Trans Med Imaging, 2013 Sep 05; 32(12). PMID: 24001988
Charisma: an integrated approach to automatic H&E-stained skeletal muscle cell segmentation using supervised learning and novel robust clump splitting.
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Med Image Anal, 2013 Sep 10; 17(8). PMID: 24012925
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DiSWOP: a novel measure for cell-level protein network analysis in localized proteomics image data.
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IEEE J Biomed Health Inform, 2014 Jan 10; 18(1). PMID: 24403407
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Med Image Comput Comput Assist Interv, 2014 Feb 08; 16(Pt 1). PMID: 24505696    Free PMC article.
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Med Image Comput Comput Assist Interv, 2014 Feb 08; 16(Pt 3). PMID: 24505787    Free PMC article.
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IEEE Trans Biomed Eng, 2014 Feb 22; 61(3). PMID: 24557687
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A novel framework for cellular tracking and mitosis detection in dense phase contrast microscopy images.
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IEEE J Biomed Health Inform, 2014 Mar 05; 17(3). PMID: 24592465
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IEEE J Biomed Health Inform, 2014 Mar 13; 18(2). PMID: 24608059
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IEEE Rev Biomed Eng, 2014 May 08; 7. PMID: 24802905
Highly Cited. Review.
Accurate diagnosis of thyroid follicular lesions from nuclear morphology using supervised learning.
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Med Image Anal, 2014 May 20; 18(5). PMID: 24835183    Free PMC article.
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IEEE Trans Biomed Eng, 2014 May 23; 61(6). PMID: 24845283
A system for counting fetal and maternal red blood cells.
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IEEE Trans Biomed Eng, 2014 Jun 01; 61(12). PMID: 24879644
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IEEE J Biomed Health Inform, 2014 Jul 24; 17(4). PMID: 25055315
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IEEE J Biomed Health Inform, 2014 Sep 06; 18(5). PMID: 25192578
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IEEE Trans Biomed Eng, 2014 Sep 30; 62(4). PMID: 25265624
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IEEE Trans Med Imaging, 2014 Oct 15; 34(2). PMID: 25314696
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IEEE Trans Biomed Circuits Syst, 2014 Nov 13; 8(5). PMID: 25388879
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Comput Med Imaging Graph, 2014 Dec 17; 42. PMID: 25498246
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Comput Med Imaging Graph, 2014 Dec 23; 42. PMID: 25529641
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IEEE Trans Biomed Eng, 2015 May 13; 62(10). PMID: 25966470
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Proc IEEE Int Symp Biomed Imaging, 2015 Sep 26; 2015. PMID: 26405506    Free PMC article.
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Machine Learning for Nuclear Mechano-Morphometric Biomarkers in Cancer Diagnosis.
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Bidirectional Mapping-Based Domain Adaptation for Nucleus Detection in Cross-Modality Microscopy Images.
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