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Search Publications by: Antonio Cardone (Fed)

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Displaying 26 - 37 of 37

Segmenting Time-lapse Phase Contrast Images of Adjacent NIH 3T3 Cells

January 15, 2013
Author(s)
Joe Chalfoun, Alden A. Dima, Marcin Kociolek, Michael W. Halter, Antonio Cardone, Adele P. Peskin, Peter Bajcsy, Mary C. Brady
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 counting

Image Classification of Vascular Smooth Muscle Cells

November 11, 2010
Author(s)
Michael Grasso, Ronil Mokashi , Alden A. Dima, Antonio Cardone, Kiran Bhadriraju, Anne L. Plant, Mary C. Brady, Yaacov Yesha, Yelena Yesha
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 was

AN AUTOMATIC OVERLAP-BASED CELL TRACKING SYSTEM

February 26, 2010
Author(s)
Joe Chalfoun, Antonio Cardone, Alden A. Dima, Michael Halter, Daniel P. Allen
In order to facilitate the extraction of quantitative data from live cell image sets, automated image analysis methods are needed. This paper presents an overlap-based cell tracking algorithm that has the ability to track cells across a set of time-lapse

Overlap-Based Cell Tracker

February 2, 2010
Author(s)
Joe Chalfoun, Antonio Cardone, Alden A. Dima, Michael Halter, Daniel P. Allen
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. This