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Search Publications by Alden A. Dima

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Displaying 1 - 25 of 34

An Informatics Infrastructure for the Materials Genome Initiative

Author(s)
Alden A. Dima, Sunil K. Bhaskarla, Chandler A. Becker, Mary C. Brady, Carelyn E. Campbell, Philippe J. Dessauw, Robert J. Hanisch, Ursula R. Kattner, Kenneth G. Kroenlein, Adele P. Peskin, Raymond L. Plante, Guillaume Sousa Amaral, Zachary T. Trautt, James A. Warren, Sharief S. Youssef, Sheng Yen Li, Pierre Francois Rigodiat, Marcus W. Newrock
A materials data infrastructure that enables the sharing and transformation of a wide range of materials data is an essential part of achieving the goals of the

Shape Descriptors Comparison for Cell Tracking

Author(s)
Michael P. Majurski, Christopher Zheng, Joe Chalfoun, Alden A. Dima, Mary C. Brady
New microscope technologies are enabling the acquisition of large volumes of live cell image data. Accurate temporal object tracking is required to facilitate

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

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

Big Data Issues in Quantitative Imaging

Author(s)
Mary C. Brady, Alden A. Dima, Charles D. Fenimore, James J. Filliben, John Lu, Adele P. Peskin, Mala Ramaiah, Ganesh Saiprasad, Ram D. Sriram

Comparison of segmentation algorithms for fluorescence microscopy images of cells

Author(s)
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
Segmentation results from nine different segmentation techniques applied to two different cell lines and five different sets of imaging conditions were compared

Predicting Segmentation Accuracy for Biological Cell Images

Author(s)
Adele P. Peskin, Alden A. Dima, Joe Chalfoun, John T. Elliott
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

Image Classification of Vascular Smooth Muscle Cells

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

AN AUTOMATIC OVERLAP-BASED CELL TRACKING SYSTEM

Author(s)
Joe Chalfoun, Antonio Cardone, Alden A. Dima, Michael W. 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 Tracker

Author(s)
Joe Chalfoun, Antonio Cardone, Alden A. Dima, Michael W. 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

A Quality Pre-Processor for Biological Cell Images

Author(s)
Adele P. Peskin, Karen Kafadar, Alden A. Dima
We have developed a method to rapidly test the quality of a biological image, to identify appropriate segmentation methods, if any, that will render high