Publications

Displaying 1 - 25 of 99

High-volume, label-free imaging for quantifying single-cell dynamics in induced pluripotent stem cell colonies

February 20, 2024

Author(s)

Anthony Asmar, Zackery Benson, Adele Peskin, Mylene Simon, Joe Chalfoun, Michael Halter, Anne L. Plant

To facilitate the characterization of unlabeled induced pluripotent stem cells (iPSCs) during culture and expansion, we developed an AI pipeline for nuclear segmentation and mitosis detection from phase contrast images of individual cells within iPSC

Semi-supervised 3D Neural Networks to Track iPS Cell Division in Label-free Phase Contrast Time Series Images

August 21, 2022

Author(s)

Adele Peskin, Joe Chalfoun, Michael Halter, Anne Plant

In order to predict cell population behavior, it is important to understand the dynamic characteristics of individual cells. Individual induced pluripotent stem (iPS) cells in colonies have been difficult to track over long times, both because segmentation

Accurate and Robust Trypan Blue-Based Cell Viability Measurement Using Neural Networks

July 19, 2021

Author(s)

Adele Peskin, Steven Lund, Chenyi Ling, Laura Pierce, Sumona Sarkar, Firdavs Kurbanov, Michael Halter, Joe Chalfoun, John T. Elliott

Trypan blue dye exclusion-based cell viability measurements are highly dependent upon image quality and consistency. In order to make measurements repeatable, one must be able to reliably capture images at a consistent focal plane, and with signal-to-noise

X-Ray Computed Tomography using Partially Coherent Fresnel Diffraction with Application to an Optical Fiber

January 18, 2021

Author(s)

Zachary H. Levine, Edward Garboczi, Adele Peskin, Axel A. Ekman, Elisabeth Mansfield, Jason Holm

An algorithm for partially coherent x-ray computed tomography including Fresnel diffraction is developed and applied to an optical fiber. The computing time is a few times worse than the projective counterpart. A code using the algorithm is used to

Detection of Dense, Overlapping, Geometric Objects

July 1, 2020

Author(s)

Adele P. Peskin, Boris Wilthan, Michael P. Majurski

Using a unique data collection, we are able to study the detection of dense geometric objects in image data where object density, clarity, and size vary. The data is a large set of black and white images of scatterplots, taken from journals reporting

Scatter corrections in x-ray computed tomography: a physics-based analysis

May 22, 2019

Author(s)

Zachary H. Levine, Timothy Blattner, Adele Peskin, Adam L. Pintar

Fundamental limits for the calculation of scattering corrections within X-ray computed tomography (CT) are found within the independent atom approximation from an analysis of the cross sections, CT geometry, and the Nyquist sampling theorem, suggesting

Multi-Energy X-Ray Tomography of an Optical Fiber: The Role of Spatial Averaging

March 14, 2019

Author(s)

Zachary H. Levine, Adele P. Peskin, Edward J. Garboczi, Andrew Holmgren

Using a commercial X-ray tomography instrument, we have obtained reconstructions of a graded-index optical fiber with voxels of edge length 1.05 µm at 12 tube voltages. The fiber manufacturer created a graded index in the central region by varying the

Progress Towards Standards for Quantitative MRI (qMRI) and Outstanding Needs

January 24, 2019

Author(s)

Kathryn E. Keenan, Joshua R. Biller, Michael A. Boss, Adele P. Peskin, Karl F. Stupic, Stephen E. Russek, Jana Delfino, Mark Does, Jeffrey L. Evelhoch, Mark Griswold, Jeffrey Gunter, R Scott Hinks, Stuart Hoffman, Geena Kim, Riccardo Lattanzi, Xiaojuan Li, Luca Marinelli, Pratik Mukherjee, Robert J. Nordstrom, Elena Perez, Berkman Sahiner, Natalie J. Serkova, Amita Shukla-Dave, Michael Steckner, Lisa J. Wilmes, Holden Wu, Huiming Zhang, Edward F. Jackson, Daniel Sullivan

The National Institute of Standards and Technology (NIST) MRI Standards project held a one-day workshop on August 4, 2017 on campus in Boulder, CO. The goal of the workshop was to evaluate the advances in quantitative MRI (qMRI) since the last NIST

Preliminary X-ray CT investigation to link Hounsfield unit measurements with the International System of Units (SI)

December 20, 2018

Author(s)

Zachary H. Levine, Adele P. Peskin, Andrew Holmgren, Edward J. Garboczi

Purpose:This paper lays the groundwork for linking Hounsfield unit measurements to the International System of Units (SI), ultimately enabling traceable measurements across X-ray CT (XCT) machines. We do this by characterizing a material basis that may be

Comparison of One-Dimensional and Volumetric Computed Tomography Measurements of Injected-Water Phantoms

September 20, 2017

Author(s)

Zachary H. Levine, Huaiyu H. Chen-Mayer, Adele P. Peskin, Adam L. Pintar

The goal of this study was to compare volumetric analysis in computed tomography (CT) with the length measurement prescribed by the Response Evaluation Criteria in Solid Tumors (RECIST) for a system with known mass and unknown shape. We injected 2 mL to 4

Classification of Journal Articles In a Search For New Experimental Thermophysical Property Data: A Case Study

June 7, 2017

Author(s)

Adele P. Peskin, Alden A. Dima

We present a case study in which we use natural language processing and machine learning techniques to automatically select candidate scientific articles that may contain new experimental thermophysical property data from thousands of articles available in

Algorithm variability in the estimation of lung nodule volume from phantom CT scans: results of the QIBA 3A public challenge

August 23, 2016

Author(s)

Adele P. Peskin, Alden A. Dima, Ganesh Saiprasad, Andrew Buckler

Quantifying changes in lung tumor volume is important for diagnosis, therapy planning, and evaluation of the response to therapy. Lung tumor volume change is determined by post-processing Computer Tomography (CT) scans of the lung, and good quantitative

An Informatics Infrastructure for the Materials Genome Initiative

July 6, 2016

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 Materials Genome Initiative. We describe two high-level requirements of such an infrastructure

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