Software for Accurate Segmentation of Cell Nuclei in Breast Tissue
Keywords: Software, cancer, pathology, screening
Background:
The Office of the Director, National Cancer Institute is seeking
statements of capability or interest from parties interested in
collaborative research (using the Cooperative Research and
Development Agreement (CRADA) or Material Transfer Agreement (MTA)
to further develop, evaluate, or commercialize the software for
accurate segmentation of cell nuclei and FISH signals in tissue
sections. Collaborators working in the field of quantitative
and automated pathology may be interested.
Description of Invention:
Automatic segmentation of cell nuclei is critical in several
high-throughput cytometry and pathology applications (1), such as
spatial analysis of genetic loci by fluorescence in situ
hybridization ("FISH"), whereas manual segmentation is laborious
(2). Current automated segmentation methods have varying
performance in the presence of distortions introduced during sample
preparation, non-uniform illumination, clustering of the individual
objects of interest (cells or cell nuclei), and seldom assess
boundary accuracy.
Researchers at the National Cancer Institute-Frederick, NIH, have
developed an automatic algorithm to segment cell nuclei (3) and
FISH signals from two-dimensional images of breast tissue. This
automated system integrates a series of advanced image processing
methods to overcome the delays inherent to current manual methods
for segmenting (delineating) individual cell nuclei in tissue
samples. The system automatically selects a subset of nuclei
that with high likelihood are accurately segmented. This system has
been validated using both simulated and actual datasets that have
been accurately analyzed by manual methods. The system
generalizes to independent analysis of many spatial parameters
useful for studying spatial gene positioning in interphase nuclei,
and potentially has a wide range of diagnostic pathology,
cytological and high throughput screening applications.
Applications:
Investigations on genomic organization (nuclear architecture and
non-random gene positioning) in the individual nuclei in
tissues.
Other pathology and cytological and high throughput screening
applications requiring precise, quantitative analysis of a subset
of cell nuclei in the sample.
Advantages:
- Automatic
- Efficient, robust and effective in extracting individual nuclei
with FISH labels
- Facilitates reproducible and unbiased spatial analysis of DNA
sequences in interphase nuclei
Development Status: Early stage
Related Publications:
(1) Prabhakar R. Gudla, J. Collins, K. Nandy, K.
J. Meaburn, T. Misteli, S. J. Lockett. A High-Throughput System for
Segmenting Nuclei Using Multiscale Techniques. Cytometry, 73A,5,
pp: 451-66, 2008.
(2) Karen J. Meaburn, Prabhakar R. Gulda, Sameena
Khan, Stephen J. Lockett and Tom Misteli. Disease-specific gene
repositioning in breast cancer. Journal of Cell Biology. Dec
14, 2009; 187 (6), pages 801-812.
(3) Kaustav Nandy, Prabhakar R. Gudla, Karen J.
Meaburn, Tom Misteli and Stephen J. Lockett. Automatic Nuclei
Segmentation And Spatial FISH Analysis For Cancer Detection.
Engineering in Medicine and Biology Society, 2009. EMBC 2009.
Annual International Conference of the IEEE 3-6 Sept. 2009 Pages:
6718-6721.
Patent Status: Research Tool. Patent
protection is not being pursued for this technology.
Contact Information:
John D. Hewes, Ph.D.
Tel. 301-435-3121
email: hewesj@mail.nih.gov
http://ttc.nci.nih.gov
Reference Number: 1085
Date: 07/09/2010
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