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Search Publications by: Joe Chalfoun (Fed)

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Displaying 26 - 42 of 42

Terabyte Size Image Computations on Hadoop Cluster Platforms

October 7, 2013
Author(s)
Peter Bajcsy, Antoine Vandecreme, Julien M. Amelot, Phuong T. Nguyen, Joe Chalfoun, Mary C. Brady
We present a characterization of four basic terabyte size image computations on a Hadoop cluster in terms of their relative efficiency according to the modified Amdahl’s law. The work is motivated by the fact that there is a lack of standard benchmarks and

A Hybrid CPU-GPU Approach to Fourier-Based Image Stitching of Optical Microscopy Images

March 3, 2013
Author(s)
Walid Keyrouz, Timothy J. Blattner, Bertrand C. Stivalet, Joe Chalfoun, Mary C. Brady, Shujia Zhou
We present a hybrid CPU-GPU approach for the Fourier-based stitching of optical microscopy images. This system achieves sub-minute stitching rates with large grids; it stitches a grid of 59x42 tiles in 26 seconds on a two-CPU (8 physical cores) & two-GPU

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

How to Select Microscopy Image Similarity Metrics?

October 10, 2012
Author(s)
Peter Bajcsy, Joe Chalfoun, Mary C. Brady
Comparisons of two microscopy images can be accomplished in many different ways. This paper presents a system that recommends appropriate similarity metrics for microscopy image comparisons based on biological application requirements. The motivation stems

Versus: A Framework for General Content-Based Comparisons

October 8, 2012
Author(s)
Peter Bajcsy, Antoine Vandecreme, Benjamin J. Long, Paul Khouri Saba, Joe Chalfoun, Luigi Marini, Rob Kooper, Michal Ondrejcek, Kenton McHenry, Smruti Padhy
Versus is a framework for the execution and dissemination of customizable content-based file comparison methods. Given digital objects such as files, database entries, or in-memory data structures, we are interested in establishing their proximity (i.e

Toward a Recommendation System for Image Similarity Metrics

October 7, 2012
Author(s)
Peter Bajcsy, Joe Chalfoun, Mary C. Brady
This paper addresses the problem of mapping application specific requirements on image similarity metrics to the plethora of existing image similarity computations. The work is motivated by the fact that there is no recommendation method for choosing a

Versus: A Framework for General Content-Based Comparisons

December 5, 2011
Author(s)
Peter Bajcsy, Antoine Vandecreme, Benjamin J. Long, Paul Khouri Saba, Joe Chalfoun, Luigi Marini, Devin Bonnie, Rob Kooper, Michal Ondrejcek, Kenton McHenry
Abstract—We present a framework for the execution and dissemination of customizable content-based file comparison methods. Given digital objects such as files, database entries, or in-memory data structures, we are interested in establishing their

Predicting Segmentation Accuracy for Biological Cell Images

December 15, 2010
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 the segmentation results and make predictions about cellular features that affect segmentation

Predicting Segmentation Accuracy for Biological Cell Images

November 29, 2010
Author(s)
Adele P. Peskin, Alden A. Dima, Joe Chalfoun
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 results from

A Human Inspired Local Ratio-Based Algorithm for Edge Detection in Fluorescent Cell Images

November 25, 2010
Author(s)
Adele P. Peskin, Joe Chalfoun, Alden A. Dima, John T. Elliott, James J. Filliben
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 algorithms

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