public data set of human vasculature

[Richard Cole]

Does anyone know of any public data sets containing human vasculature?  We are currently developing tracing algorithms for vasculature.    These algorithms  are being developed for intra-vital MP confocal sets (mice), but we would like to see if they could be adapted to work with another imaging modality. 

 

 

Thanks

 

Rich

 

Richard Cole
Research Scientist V
Director: Advanced Light Microscopy Core Unit
Wadsworth Center

 

Research Assistant Professor
Dept. of Biomedical Sciences
School of Public Health State University of New York

P.O. Box 509 Albany N.Y. 12201-0509
518-474-7048 Phone
518-474-4430 Fax

 

Email [hidden email]

Website www.wadsworth.org/cores/alm/index.htm

 

 

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[Mario-2]

Richard,

This is a shot in the dark, but I am guessing that someone at the University of Washington Vascular Imaging Lab could possibly get you the information you need.

The Vascular Imaging Lab
University of Washington
815 Mercer Street
Box 358050

Seattle, WA 98109

Phone: [phone]
Fax: [phone]
Email: [hidden email]

If it is not this group then it maybe another at UW. Once upon a time there was a group at UW that was heavily involved in computer simulation studies of capillary structures and blood flow.

You might check them out.

Mario

Does anyone know of any public data sets containing human vasculature?  We are currently developing tracing algorithms for vasculature.    These algorithms  are being developed for intra-vital MP confocal sets (mice), but we would like to see if they could be adapted to work with another imaging modality.

 

 

Thanks

 

Rich

 

Richard Cole
Research Scientist V
Director: Advanced Light Microscopy Core Unit
Wadsworth Center

 

Research Assistant Professor
Dept. of Biomedical Sciences
School of Public Health State University of New York

P.O. Box 509 Albany N.Y. 12201-0509
518-474-7048 Phone
518-474-4430 Fax

 

Email [hidden email]

Website www.wadsworth.org/cores/alm/index.htm

 

 

IMPORTANT NOTICE: This e-mail and any attachments may contain
confidential or sensitive information which is, or may be, legally
privileged or otherwise protected by law from further disclosure. It
is intended only for the addressee. If you received this in error or
from someone who was not authorized to send it to you, please do not
distribute, copy or use it or any attachments. Please notify the
sender immediately by reply e-mail and delete this from your
system. Thank you for your cooperation.

-- 

________________________________________________________________________________
Mario M. Moronne, Ph.D.

[hidden email]
[hidden email]

[George McNamara]

Hi Rich,

FARsight project, http://www.farsight-toolkit.org/wiki/Main_Page see http://www.farsight-toolkit.org/wiki/Special:FarsightDownloads types of download: data sets (Zeiss LSM files ... Badri should be able to send you more data), and first paper:


Neurosci Methods. 2008 May 15;170(1):165-78. Epub 2008 Jan 17.

Associative image analysis: a method for automated quantification of 3D multi-parameter images of brain tissue.

Bjornsson CS, Lin G, Al-Kofahi Y, Narayanaswamy A, Smith KL, Shain W, Roysam B.

Center for Neural Communication Technology, New York State Department of Health, Wadsworth Center, Albany, NY 12201-0509, USA.

Abstract

Brain structural complexity has confounded prior efforts to extract quantitative image-based measurements. We present a systematic 'divide and conquer' methodology for analyzing three-dimensional (3D) multi-parameter images of brain tissue to delineate and classify key structures, and compute quantitative associations among them. To demonstrate the method, thick ( approximately 100 microm) slices of rat brain tissue were labeled using three to five fluorescent signals, and imaged using spectral confocal microscopy and unmixing algorithms. Automated 3D segmentation and tracing algorithms were used to delineate cell nuclei, vasculature, and cell processes. From these segmentations, a set of 23 intrinsic and 8 associative image-based measurements was computed for each cell. These features were used to classify astrocytes, microglia, neurons, and endothelial cells. Associations among cells and between cells and vasculature were computed and represented as graphical networks to enable further analysis. The automated results were validated using a graphical interface that permits investigator inspection and corrective editing of each cell in 3D. Nuclear counting accuracy was >89%, and cell classification accuracy ranged from 81 to 92% depending on cell type. We present a software system named FARSIGHT implementing our methodology. Its output is a detailed XML file containing measurements that may be used for diverse quantitative hypothesis-driven and exploratory studies of the central nervous system.

PMID: 18294697



George


At 12:31 PM 8/16/2010, you wrote:

Does anyone know of any public data sets containing human vasculature?  We are currently developing tracing algorithms for vasculature.    These algorithms  are being developed for intra-vital MP confocal sets (mice), but we would like to see if they could be adapted to work with another imaging modality. 
 
 
Thanks
 
Rich
 
Richard Cole
Research Scientist V
Director: Advanced Light Microscopy Core Unit
Wadsworth Center
 
Research Assistant Professor
Dept. of Biomedical Sciences
School of Public Health State University of New York

P.O. Box 509 Albany N.Y. 12201-0509
518-474-7048 Phone
518-474-4430 Fax
 
Email [hidden email]
Website www.wadsworth.org/cores/alm/index.htm