Automated segmentation of cancer cell nuclei in complex tissue sections

2001 ◽  
Author(s):  
Constantinos G. Loukas ◽  
George D. Wilson ◽  
Borivoj Vojnovic
Keyword(s):  
Cancer Cell ◽  
Automated Segmentation ◽  
Cell Nuclei ◽  
Tissue Sections

scholarly journals An image analysis-based approach for automated counting of cancer cell nuclei in tissue sections

Cytometry ◽  
2003 ◽  
Vol 55A (1) ◽  
pp. 30-42 ◽  
Author(s):  
Constantinos G. Loukas ◽  
George D. Wilson ◽  
Borivoj Vojnovic ◽  
Alf Linney
Keyword(s):  
Image Analysis ◽  
Cancer Cell ◽  
Cell Nuclei ◽  
Tissue Sections

Crisp and soft multivariate methods visualize individual cell nuclei in Raman images of liver tissue sections

2011 ◽  
Vol 55 (1) ◽  
pp. 90-100 ◽  
Author(s):  
Christoph Krafft ◽  
Mehrnaz Alipour Diderhoshan ◽  
Peter Recknagel ◽  
Milos Miljkovic ◽  
Michael Bauer ◽  
...  
Keyword(s):  
Liver Tissue ◽  
Individual Cell ◽  
Multivariate Methods ◽  
Cell Nuclei ◽  
Tissue Sections

Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy

2012 ◽  
Vol 5 (11-12) ◽  
pp. 878-888 ◽  
Author(s):  
Anna Medyukhina ◽  
Tobias Meyer ◽  
Michael Schmitt ◽  
Bernd F. M. Romeike ◽  
Benjamin Dietzek ◽  
...  
Keyword(s):  
Optical Microscopy ◽  
Nonlinear Optical ◽  
Automated Segmentation ◽  
Cell Nuclei ◽  
Nonlinear Optical Microscopy

scholarly journals An image dataset related to automated macrophage detection in immunostained lymphoma tissue samples

GigaScience ◽  
2020 ◽  
Vol 9 (3) ◽  
Author(s):  
Marcus Wagner ◽  
Sarah Reinke ◽  
René Hänsel ◽  
Wolfram Klapper ◽  
Ulf-Dietrich Braumann
Keyword(s):  
Reference Method ◽  
Image Data ◽  
B Cell Lymphoma ◽  
Automated Image Analysis ◽  
Large Set ◽  
Cell Nuclei ◽  
Tissue Samples ◽  
Automated Recognition ◽  
Tissue Sections ◽  
Image Dataset

Abstract Background We present an image dataset related to automated segmentation and counting of macrophages in diffuse large B-cell lymphoma (DLBCL) tissue sections. For the classification of DLBCL subtypes, as well as for providing a prognosis of the clinical outcome, the analysis of the tumor microenvironment and, particularly, of the different types and functions of tumor-associated macrophages is indispensable. Until now, however, most information about macrophages has been obtained either in a completely indirect way by gene expression profiling or by manual counts in immunohistochemically (IHC) fluorescence-stained tissue samples while automated recognition of single IHC stained macrophages remains a difficult task. In an accompanying publication, a reliable approach to this problem has been established, and a large set of related images has been generated and analyzed. Results Provided image data comprise (i) fluorescence microscopy images of 44 multiple immunohistostained DLBCL tumor subregions, captured at 4 channels corresponding to CD14, CD163, Pax5, and DAPI; (ii) ”cartoon-like” total variation–filtered versions of these images, generated by Rudin-Osher-Fatemi denoising; (iii) an automatically generated mask of the evaluation subregion, based on information from the DAPI channel; and (iv) automatically generated segmentation masks for macrophages (using information from CD14 and CD163 channels), B-cells (using information from Pax5 channel), and all cell nuclei (using information from DAPI channel). Conclusions A large set of IHC stained DLBCL specimens is provided together with segmentation masks for different cell populations generated by a reference method for automated image analysis, thus featuring considerable reuse potential.

A bioartificial rat heart tissue: Perfusion decellularization and characterization

2019 ◽  
Vol 42 (12) ◽  
pp. 757-764 ◽  
Author(s):  
Busra Ozlu ◽  
Mert Ergin ◽  
Sevcan Budak ◽  
Selcuk Tunali ◽  
Nuh Yildirim ◽  
...  
Keyword(s):  
Extracellular Matrix ◽  
Three Dimensional ◽  
Tissue Perfusion ◽  
Heart Tissue ◽  
Cell Nuclei ◽  
Tissue Sections ◽  
The Past ◽  
Significant Difference ◽  
Structural Preservation

Despite remarkable advancement in the past decades, heart-related defects are still prone to progress irreversibly and can eventually lead to heart failure. A personalized extracellular matrix–based bioartificial heart created by allografts/xenografts emerges as an alternative as it can retain the original three-dimensional architecture combined with a preserved natural heart extracellular matrix. This study aimed at developing a procedure for decellularizing heart tissue harvested from rats and evaluating decellularization efficiency in terms of residual nuclear content and structural properties. Tissue sections showed no or little visible cell nuclei in decellularized heart, whereas the native heart showed dense cellularity. In addition, there was no significant variation in the alignment of muscle fibers upon decellularization. Furthermore, no significant difference was detected between native and decellularized hearts in terms of fiber diameter. Our findings demonstrate that fiber alignment and diameter can serve as additional parameters in the characterization of biological heart scaffolds as these provide valuable input for evaluating structural preservation of decellularized heart. The bioartificial scaffold formed here can be functionalized with patient’s own material and utilized in regenerative engineering.

scholarly journals Segmentation of confocal microscope images of cell nuclei in thick tissue sections

1999 ◽  
Vol 193 (3) ◽  
pp. 212-226 ◽  
Author(s):  
C. ORTIZ DE SOLORZANO ◽  
E. GARCIA RODRIGUEZ ◽  
A. JONES ◽  
D. PINKEL ◽  
J. W. GRAY ◽  
...  
Keyword(s):  
Confocal Microscope ◽  
Cell Nuclei ◽  
Tissue Sections ◽  
Microscope Images
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