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Improving the Robustness of Cell Nucleus Segmentation
1998
Procedings of the British Machine Vision Conference 1998
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A highly successful active contour implementation, for the automatic segmentation of cervical cell nuclei, is shown to lend itself well to a framework that further increases its success rate. ...
Only one object of interest is contained in the image, but as artefacts often appear as well, the contour varies with the parameter as it finds different solutions. ...
The failures due to the presence of the background in the nucleus images were deemed to be preventable at a previous cell-finding stage. ...
doi:10.5244/c.12.52
dblp:conf/bmvc/BamfordL98
fatcat:ao52x273tfhdrbcxdmrz7emxfy
Unsupervised Segmentation Based on Robust Estimation and Color Active Contour Models
2005
IEEE Transactions on Information Technology in Biomedicine
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cells. ...
In this paper, we investigate the design, development, and implementation of a robust color gradient vector flow (GVF) active contour model for performing segmentation, using a database of 1791 imaged ...
ACKNOWLEDGMENT The authors are extremely grateful to Dr. A. Bagg, Dr. M. Feldman, and Dr. S. Gheith from the Hospital of the University of Pennsylvania, and Dr. L. Goodell and Dr. G. ...
doi:10.1109/titb.2005.847515
pmid:16167702
fatcat:hu76klwgirdjpdwkvxaepm3bnq
Various Techniques for Classification and Segmentation of Cervical Cell Images - A Review
2016
International Journal of Computer Applications
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The nucleus segmentation varies as: single-nucleus segmentation, touching-nuclei splitting and multiple-nuclei segmentation. ...
The shortcomings and failures of the existing work are also provided for further enhancement and improvement of overall performance and accuracy. ...
Using MSCN , segmentation performance is improved by 27.42%, and the nucleus segmentation accuracy is improved by 35.09% compared with SSCN. ...
doi:10.5120/ijca2016911170
fatcat:aawlez3kvngffopg6wgj36ormq
Automatic cell segmentation in fluorescence images of confluent cell monolayers using multi-object geometric deformable model
2013
Medical Imaging 2013: Image Processing
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curvature based image operator. 3) The final segmentation using MGDM promotes robust and accurate segmentation results, and guarantees no overlaps and gaps between neighboring cells. ...
Despite substantial progress, there is still a need to improve the accuracy, efficiency, and adaptability to different cell morphologies. ...
Future work would involve: 1) incorporating region and shape prior of cells in MGDM to further improve the robustness and accuracy of the algorithm; 2) introduce a belief measure for each segmented cell ...
doi:10.1117/12.2006603
pmid:24386546
pmcid:PMC3877311
dblp:conf/miip/YangBCYSP13
fatcat:v43wpdv73bh5bcbdwfr5nfzon4
White Blood Cell Segmentation via Sparsity and Geometry Constraints
2019
IEEE Access
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Our model fitting strategy is able to significantly improve the robustness of the proposed segmentation algorithm against outliers that could seriously contaminate WBCs. ...
In particular, the effective segmentation of White Blood Cells (WBCs) remains a challenging problem due to the blurring boundaries of WBCs under rapid staining, as well as the adhesion between leukocytes ...
to improve the robustness and effectiveness of WBC segmentation for detecting incomplete cell boundaries. ...
doi:10.1109/access.2019.2954457
fatcat:vd2fkb2m6ffr3b44c4fasieasa
Graph-based segmentation of abnormal nuclei in cervical cytology
2017
Computerized Medical Imaging and Graphics
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A general method is reported for improving the segmentation of abnormal cell nuclei in cervical cytology images. ...
Despite some progress, there is a need to improve the sensitivity, particularly the segmentation of abnormal nuclei. ...
Acknowledgments This work was supported in part by the NIH Grant R01EB004640, the National Natural Science Foundation of China61427806 and 81501545, and the China Postdoctoral Science Foundation Grant ...
doi:10.1016/j.compmedimag.2017.01.002
pmid:28222324
pmcid:PMC5777156
fatcat:yri2suebr5h3vpmz6h2vyw5hbi
Combining fully convolutional networks and graph-based approach for automated segmentation of cervical cell nuclei
2017
2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)
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The map is formulated into the graph cost function in addition to the properties of the nucleus border and nucleus region. ...
The globally optimal path in the constructed graph is identified by dynamic programming. Validation of our method was performed on cell nuclei from Herlev Pap smear dataset. ...
This research was supported by the Intramural Research Program of the National Institutes of Health Clinical Center. The authors thank Nvidia for the TITAN Z GPU donation. ...
doi:10.1109/isbi.2017.7950548
dblp:conf/isbi/ZhangSLSY17
fatcat:d2dqp37yd5gdvc46pk4j7r4xae
Review of Nuclei Detection, Segmentation in Microscopic Images
2017
Journal of Bioengineering and Biomedical Sciences
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This paper is a review of some recent state-of-art nucleus/cell segmentation approaches on different types of microscopic images. ...
We and discussed and studied here various trends on nucleus detection, and segmentation. ...
Hence it should preserve the shape of cell nucleus based on nuclear shape model and prevent two or more nuclei from being merged. ...
doi:10.4172/2155-9538.1000227
fatcat:xxvyqhsghzgplddods4bjlulq4
New decision support tool for acute lymphoblastic leukemia classification
2012
Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II
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The system is further tested on the classification of spectra measured from the cell nuclei in blood samples in order to distinguish normal cells from those affected by Acute Lymphoblastic Leukemia. ...
By performing K-means clustering on the resultant images, the nuclei of the cells under consideration are obtained. Shape features and texture features are then extracted for classification. ...
that utilizes both intensity and shape information of cell to improve the segmentation was proposed by Wang et al ...
doi:10.1117/12.905969
dblp:conf/ipas/MadhukarAC12
fatcat:4gbm5hbnxvav7inm3pas6wvp3y
Detection of Perlger-Huet anomaly based on augmented fast marching method and speeded up robust features
2015
Bio-medical materials and engineering
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Then, caryoplastin in the nucleus is extracted based on Speeded Up Robust Features (SURF) and a K-nearest-neighbor (KNN) classifier is constructed to analyze the features. ...
Meanwhile, the detection method should be helpful to the automatic morphological classification of blood cells. ...
In addition, recognition of the nucleolar region should be added to improve the detection. Fig. 1 . 1 a, b, c) Pelger-Huet cells (PHC), d, e) pseudo Pelger-Huet cells (PPHC). ...
doi:10.3233/bme-151421
pmid:26405883
fatcat:c6y7krolkbfopbbrpbvmch6xs4
Neural Network Segmentation of Cell Ultrastructure Using Incomplete Annotation
[article]
2020
arXiv
pre-print
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For scalable modeling of beta cell ultrastructure, we investigate automatic segmentation of whole cell imaging data acquired through soft X-ray tomography. ...
To more effectively use existing annotations, we propose a method that enables the application of partially labeled data for full label segmentation. ...
The improvement for these labels also suggests that a more robust knowledge of the distribution on one set of structures in the cell can inform the inference of others. ...
arXiv:2004.09673v1
fatcat:2kxypy6kbrgffcgekklhrqm2de
Extracting neuronal activity signals from microscopy recordings of contractile tissue using B-spline Explicit Active Surfaces (BEAS) cell tracking
2021
Scientific Reports
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The latter takes advantage of the appearance of GCaMP expressing cells, and tracks the nucleus' boundaries together with the cytoplasmic contour, providing a stable delineation of neighboring, overlapping ...
This improves the total yield of efficacious cell tracking and allows signal extraction from other cell compartments like neuronal processes. ...
Acknowledgements The authors thank Tobie Martens for manual cell delineation and ROI selection on Ca 2+ recordings. such there was no direct use of animal tissues for this study. ...
doi:10.1038/s41598-021-90448-4
pmid:34035411
pmcid:PMC8149687
fatcat:i7dlvchi55awtdgnasqwyep6yi
Extracting 3D cell parameters from dense tissue environments: application to the development of the mouse heart
2013
Computer applications in the biosciences : CABIOS
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Results: We propose an automated framework for the segmentation of 3D microscopy images of highly cluttered environments such as developing tissues. ...
cell division and cell polarity through the creation of 3D orientation maps that provide novel insight into tissue organization during organogenesis. ...
The proposed framework combines a number of robust PDE-derived approaches that jointly exploit nucleus and cell fluorescence information, and provides an efficient toolset for robust quantification of ...
doi:10.1093/bioinformatics/btt027
pmid:23337749
fatcat:lsusbdbba5epdi4csdjm23bf5q
Scalable system for classification of white blood cells from Leishman stained blood stain images
2013
Journal of Pathology Informatics
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Active contours are employed for robust segmentation of the WBC nucleus and cytoplasm. The seed points are generated by processing the images in Hue-Saturation-Value (HSV) color space. ...
The digitized microscopic images are stain normalized for the segmentation, to be consistent over a diverse set of slide images. ...
Cytoplasm Segmentation Cytoplasm segmentation required the extraction of white blood cells. The nucleus was then subtracted from the obtained WBC to get the cytoplasm. ...
doi:10.4103/2153-3539.109883
pmid:23766937
pmcid:PMC3678750
fatcat:nsq3w2d6xrfmjpajcrqkvqhzhi
White blood cell segmentation using morphological operators and scale-space analysis
2007
XX Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI 2007)
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In this paper, we propose a novel method to segment nucleus and cytoplasm of white blood cells (WBC). ...
Cell segmentation is a challenging problem due to both the complex nature of the cells and the uncertainty present in video microscopy. ...
In this paper, our focus is the segmentation of white blood cells (WBC), also called leukocytes [1] . ...
doi:10.1109/sibgrapi.2007.33
dblp:conf/sibgrapi/DoriniML07
fatcat:fojokdzajrdyvbpfmlzvroycn4
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