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5. Focus prediction in digital holographic microscopy using deep convolutional neural networks

Author

Pitkäaho, T. (Tomi), Manninen, A. (Aki), Naughton, T. J. (Thomas J.), Pitkäaho, T. (Tomi), Manninen, A. (Aki), and Naughton, T. J. (Thomas J.)

Abstract

Deep artificial neural network learning is an emerging tool in image analysis. We demonstrate its potential in the field of digital holographic microscopy by addressing the challenging problem of determining the in-focus reconstruction depth of Madin–Darby canine kidney cell clusters encoded in digital holograms. A deep convolutional neural network learns the in-focus depths from half a million hologram amplitude images. The trained network correctly determines the in-focus depth of new holograms with high probability, without performing numerical propagation. This paper reports on extensions to preliminary work published earlier as one of the first applications of deep learning in the field of digital holographic microscopy.

Published
2019

8. Focus classification in digital holographic microscopy using deep convolutional neural networks

Author

Pitkäaho, T. (Tomi), Manninen, A. (Aki), Naughton, T. J. (Thomas J.), Pitkäaho, T. (Tomi), Manninen, A. (Aki), and Naughton, T. J. (Thomas J.)

Abstract

In digital holographic microscopy, one often obtains an in-focus image of the sample by applying a focus metric to a stack of numerical reconstructions. We present an alternative approach using a deep convolutional neural network.

Published
2017

9. Nonparametric Multivariate Anomaly Analysis in Support of HPC Resilience

Author

Ostrouchov, George Ornl, Naughton, III Thomas J. Ornl, Naughton, T., Engelmann, Christian Ornl, Vallee, Geoffroy R. Ornl, and Scott, Stephen L. Ornl

Abstract

Large-scale computing systems provide great potential for scientific exploration. However, the complexity that accompanies these enormous machines raises challenges for both, users and operators. The effective use of such systems is often hampered by failures encountered when running applications on systems containing tens-of-thousands of nodes and hundreds-of-thousands of compute cores capable of yielding petaflops of performance. In systems of this size failure detection is complicated and root-cause diagnosis difficult. This paper describes our recent work in the identification of anomalies in monitoring data and system logs to provide further insights into machine status, runtime behavior, failure modes and failure root causes. It discusses the details of an initial prototype that gathers the data and uses statistical techniques for analysis.

Published
2010

10. Implementations of a model of physical sorting

Author

Murphy, N., Naughton, T. J., Woods, D., Beverley M. Henley, Mcdermott, K., Duffy, E., Burgt, P. J. M., and Woods, N.

Abstract

We define a computational model of physical devices that have a parallel atomic operation that transforms their input, an unordered list, in such a way that their output, the sorted list, can be sequentially read off in linear time. We show that several commonly-used scientific laboratory techniques (from biology, chemistry, and physics) are instances of the model and we provide experimental implementations.

Published
2007

11. Analysis of partially occluded objects encoded in digital holograms using the Wigner distribution function

Author

Hennelly, B. M., Maycock, Jonathan, McElhinney, Conor P., Naughton, T. J., McDonald, J. B., and Javidi, B.

Subjects
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

In this paper, we analysis the effect of partial occlusions in scenes captured using digital holography. We reconstruct the scene from different perspectives. These reconstructions are then combined, allowing one to overcome foreground occlusions that are obscuring one’s view of the scene. The analysis in this paper is carried out with the aid of the Wigner distribution function, allowing us to visualize the energy of the object wavefield and the occluding object wavefield in phase space. We show that by iteratively selecting different views, the original scene can be reconstructed efficiently. This technique would be useful in situations where transmission of the whole digital hologram, or exhaustive reconstruction of every perspective, was not feasible. We provide results using optically captured digital holograms of real-world objects, and simulated occlusions.

Published
2006

12. P-26 B-Type Natriuretic Peptide Testing and the Accuracy of Heart Failure Diagnosis in the Emergency Department

Author

Jacob Federman, Hans G. Schneider, Amaali Lokuge, Naughton T. Matthew, David Eccleston, De Villiers Smit, Adam Bystrzycki, Louisa Lok Yi Lam, Krum Henry, Genevieve Flannery, and Peter Cameron

Subjects
Community and Home Care, medicine.medical_specialty, Epidemiology, business.industry, Internal medicine, Heart failure, medicine, Cardiology, Emergency department, Cardiology and Cardiovascular Medicine, business, Natriuretic peptide testing, medicine.disease
Published
2009
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24. Scalable system software: a component-based approach

Author

Bode, B, primary, Bradshaw, R, additional, DeBenedictus, E, additional, Desai, N, additional, Duell, J, additional, Geist, G A, additional, Hargrove, P, additional, Jackson, D, additional, Jackson, S, additional, Laros, J, additional, Lowe, C, additional, Lusk, E, additional, McLendon, W, additional, Mugler, J, additional, Naughton, T, additional, Navarro, J P, additional, Oldfield, R, additional, Pundit, N, additional, Scott, S L, additional, Showerman, M, additional, Steffen, C, additional, and Walker, K, additional

Published
2005
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43. Implementations of a Model of Physical Sorting.

Author

Murphy, N., Naughton, T. J., Woods, D., Henley, B., McDermott, K., Duffy, E., van der Burgt, P. J. M., and Woods, N.

Subjects
LIFE sciences, OPTICS, MASS spectrometry, ELECTRONIC data processing, LIFE science education, LABORATORY techniques
Abstract

We define a model of physical devices that have a parallel atomic operation that transforms an unordered list input such that the sorted output can be sequentially read off in linear time. We show that commonly used biology, chemistry, and physics laboratory techniques are model instances and provide implementations. [ABSTRACT FROM AUTHOR]

Published
2008

44. Compression of Optically Encrypted Digital Holograms Using Artificial Neural Networks.

Author

Shortt, A. E., Naughton, T. J., and Javidi, B.

Abstract

Compression and encryption/decryption are necessary for secure and efficient storage and transmission of image data. Optical encryption, as a promising application of display devices, takes advantage of both the massive parallelism inherent in optical systems and the flexibility offered by digital electronics. We encrypt real-world three-dimensional (3D) objects, captured using phase-shift interferometry, by combining a phase mask and Fresnel propagation. Compression is achieved by nonuniformly quantizing the complex-valued encrypted digital holograms using an artificial neural network. Decryption is performed by displaying the encrypted hologram and phase mask in an identical configuration. We achieved good quality decryption and reconstruction of 3D objects with as few as 2 bits in each real and imaginary value of the encrypted data [ABSTRACT FROM PUBLISHER]

Published
2006
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