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A novel dictionary based computer vision method for the detection of cell nuclei

Jonas De Vylder, Jan Aelterman UGent, Trees Lepez UGent, Mado Vandewoestyne UGent, Koen Douterloigne, Dieter Deforce UGent and Wilfried Philips UGent (2013) PLOS ONE. 8(1).
abstract
Cell nuclei detection in fluorescent microscopic images is an important and time consuming task in a wide range of biological applications. Blur, clutter, bleed through and partial occlusion of nuclei make individual nuclei detection a challenging task for automated image analysis. This paper proposes a novel and robust detection method based on the active contour framework. Improvement over conventional approaches is achieved by exploiting prior knowledge of the nucleus shape in order to better detect individual nuclei. This prior knowledge is defined using a dictionary based approach which can be formulated as the optimization of a convex energy function. The proposed method shows accurate detection results for dense clusters of nuclei, for example, an F-measure (a measure for detection accuracy) of 0.96 for the detection of cell nuclei in peripheral blood mononuclear cells, compared to an F-measure of 0.90 achieved by state-of-the-art nuclei detection methods.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
SOFTWARE, EXTRACTION, SHAPE PRIOR, IMAGE SEGMENTATION, ACTIVE CONTOUR MODEL, MICROSCOPY, TRACKING, CIRCLES, GAS
journal title
PLOS ONE
PLoS One
volume
8
issue
1
article number
e54068
pages
9 pages
Web of Science type
Article
Web of Science id
000314023600028
JCR category
MULTIDISCIPLINARY SCIENCES
JCR impact factor
3.534 (2013)
JCR rank
8/55 (2013)
JCR quartile
1 (2013)
ISSN
1932-6203
DOI
10.1371/journal.pone.0054068
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
3109791
handle
http://hdl.handle.net/1854/LU-3109791
date created
2013-01-28 10:32:49
date last changed
2016-12-21 15:42:35
@article{3109791,
  abstract     = {Cell nuclei detection in fluorescent microscopic images is an important and time consuming task in a wide range of biological applications. Blur, clutter, bleed through and partial occlusion of nuclei make individual nuclei detection a challenging task for automated image analysis. This paper proposes a novel and robust detection method based on the active contour framework. Improvement over conventional approaches is achieved by exploiting prior knowledge of the nucleus shape in order to better detect individual nuclei. This prior knowledge is defined using a dictionary based approach which can be formulated as the optimization of a convex energy function. The proposed method shows accurate detection results for dense clusters of nuclei, for example, an F-measure (a measure for detection accuracy) of 0.96 for the detection of cell nuclei in peripheral blood mononuclear cells, compared to an F-measure of 0.90 achieved by state-of-the-art nuclei detection methods.},
  articleno    = {e54068},
  author       = {De Vylder, Jonas and Aelterman, Jan and Lepez, Trees and Vandewoestyne, Mado and Douterloigne, Koen and Deforce, Dieter and Philips, Wilfried},
  issn         = {1932-6203},
  journal      = {PLOS ONE},
  keyword      = {SOFTWARE,EXTRACTION,SHAPE PRIOR,IMAGE SEGMENTATION,ACTIVE CONTOUR MODEL,MICROSCOPY,TRACKING,CIRCLES,GAS},
  language     = {eng},
  number       = {1},
  pages        = {9},
  title        = {A novel dictionary based computer vision method for the detection of cell nuclei},
  url          = {http://dx.doi.org/10.1371/journal.pone.0054068},
  volume       = {8},
  year         = {2013},
}

Chicago
De Vylder, Jonas, Jan Aelterman, Trees Lepez, Mado Vandewoestyne, Koen Douterloigne, Dieter Deforce, and Wilfried Philips. 2013. “A Novel Dictionary Based Computer Vision Method for the Detection of Cell Nuclei.” Plos One 8 (1).
APA
De Vylder, Jonas, Aelterman, J., Lepez, T., Vandewoestyne, M., Douterloigne, K., Deforce, D., & Philips, W. (2013). A novel dictionary based computer vision method for the detection of cell nuclei. PLOS ONE, 8(1).
Vancouver
1.
De Vylder J, Aelterman J, Lepez T, Vandewoestyne M, Douterloigne K, Deforce D, et al. A novel dictionary based computer vision method for the detection of cell nuclei. PLOS ONE. 2013;8(1).
MLA
De Vylder, Jonas, Jan Aelterman, Trees Lepez, et al. “A Novel Dictionary Based Computer Vision Method for the Detection of Cell Nuclei.” PLOS ONE 8.1 (2013): n. pag. Print.