A two-layer structure prediction framework for microscopy cell detection

A two-layer structure prediction framework for microscopy cell detection

Highlights • A new two-layer structural prediction framework for detecting microscopic image cells, which focuses on the representation issue to propose a model to effectively capture the rich contextual information. • We tackle the problem of microscopic image cell detection from structure learning...

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Veröffentlicht in:Computerized medical imaging and graphics 2015-04, Vol.41, p.29-36
Hauptverfasser: Xu, Yan, Wu, Weiying, Chang, Eric I-Chao, Chen, Danny, Mu, Jian, Lee, Peter P, Blenman, Kim R.M, Tu, Zhuowen
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Breast Neoplasms - pathology
Cell Tracking - methods
Computer vision
Female
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Internal Medicine
Layered models
Lymph Nodes - pathology
Lymphatic Metastasis
Machine Learning
Microscopy - methods
Microscopy cell detection
Other
Pattern Recognition, Automated - methods
Reproducibility of Results
Sensitivity and Specificity
Structural prediction
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Beschreibung
Zusammenfassung:Highlights • A new two-layer structural prediction framework for detecting microscopic image cells, which focuses on the representation issue to propose a model to effectively capture the rich contextual information. • We tackle the problem of microscopic image cell detection from structure learning perspective. • The second layer takes the output of the first layer as knowledge abstraction and propagation.
ISSN:0895-6111
1879-0771
DOI:10.1016/j.compmedimag.2014.07.001