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Author: alden dima
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Displaying records 1 to 10 of 22 records.
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1. Segmenting Time-lapse Phase Contrast Images of Adjacent NIH 3T3 Cells
Published: 1/15/2013
Authors: Joe Chalfoun, Alden A Dima, Marcin Kociolek, Michael W Halter, Antonio Cardone, Adele P Peskin, Peter Bajcsy, Mary C Brady
Abstract: We present a new method for segmenting phase contrast images of NIH 3T3 fibroblast cells that is accurate even when cells are in contact. The problem of segmentation, when cells are in contact, poses a challenge to the accurate automation of cell cou ...
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=910670

2. Big Data Issues in Quantitative Imaging
Series: OTHER
Published: 8/29/2012
Authors: Mary C Brady, Alden A Dima, Charles D. Fenimore, James J Filliben, John Lu, Adele P Peskin, Mala Ramaiah, Ganesh Saiprasad, Ram D Sriram
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=911670

3. An Automated Method for Locating Phantom Nodules in Anthropomorphic Thoracic Phantom CT Studies
Published: 7/19/2012
Authors: Adele P Peskin, Alden A Dima, Ganesh Saiprasad
Abstract: The Cancer Imaging Archive (TCIA) has a publically available FDA database consisting of just over thousand CT scans intended for facilitating the assessment of lung nodule size estimation methodologies, the development of image analysis software, as ...
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=911057

4. Developing an Informatics and Database Infrastructure for Proficiency Testing of Quantitative Imaging Algorithms
Published: 9/23/2011
Author: Alden A Dima
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=909535

5. Comparison of segmentation algorithms for fluorescence microscopy images of cells
Published: 6/14/2011
Authors: Alden A Dima, John T Elliott, James J Filliben, Michael W Halter, Adele P Peskin, Javier Bernal, Marcin Kociolek, Mary C Brady, Hai C. Tang, Anne L Plant
Abstract: Segmentation results from nine different segmentation techniques applied to two different cell lines and five different sets of imaging conditions were compared. Significant variability in the results of segmentation was observed that was due solely ...
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=905998

6. Predicting Segmentation Accuracy for Biological Cell Images
Published: 12/15/2010
Authors: Adele P Peskin, Alden A Dima, Joe Chalfoun, John T Elliott
Abstract: We have performed segmentation procedures on a large number of images from two mammalian cell lines that were seeded at low density, in order to study trends in the segmentation results and make predictions about cellular features that affect segm ...
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=906721

7. Predicting Segmentation Accuracy for Biological Cell Images
Published: 11/29/2010
Authors: Adele P Peskin, Alden A Dima, Joe Chalfoun
Abstract: We have performed image segmentations on a very large number of images, using a wide variety of imaging conditions and cell lines, in order to study trends in the segmentation results and make predictions about segmentation accuracy. Comparing result ...
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=904744

8. A Human Inspired Local Ratio-Based Algorithm for Edge Detection in Fluorescent Cell Images
Published: 11/25/2010
Authors: Adele P Peskin, Joe Chalfoun, Alden A Dima, John T Elliott, James J Filliben
Abstract: We have developed a new semi-automated method for segmenting images of biological cells seeded at low density on tissue culture substrates, which we use to improve the generation of reference data for the evaluation of automated segmentation algor ...
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=906723

9. Image Classification of Vascular Smooth Muscle Cells
Published: 11/11/2010
Authors: Michael Grasso, Ronil Mokashi , Alden A Dima, Antonio Cardone, Kiran Bhadriraju, Anne L Plant, Mary C Brady, Yaacov Yesha, Yelena Yesha
Abstract: The traditional method of cell microscopy can be subjective, due to observer variability, a lack of standardization, and a limited feature set. To address this challenge, we developed an image classifier using a machine learning approach. Our system ...
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=905981

10. Overlap-Based Cell Tracker
Series: NIST Interagency/Internal Report (NISTIR)
Report Number: 7663
Published: 2/2/2010
Authors: Joe Chalfoun, Antonio Cardone, Alden A Dima, Michael W Halter, Daniel P Allen
Abstract: In order to facilitate the extraction of quantitative data from live cell image sets, automated image analysis methods are needed. This paper presents an introduction to the general principle of an overlap cell tracking software developed by NIST. Th ...
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=904008



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