Dr. Daniel J. Tward Profile

Dr. Daniel J. Tward

Postdoctoral Fellow at Johns Hopkins Univ

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Publications (9)

Proceedings Article | 22 March 2016 Paper

Eigenbreasts for statistical breast phantoms

Gregory Sturgeon, Daniel Tward, M. Ketcha, J. Ratnanather, M. Miller, Subok Park, W. Segars, Joseph Lo

Proceedings Volume 9783, 97832B (2016) https://doi.org/10.1117/12.2216398

KEYWORDS: Breast, Breast imaging, Principal component analysis, Mammography, Clinical trials, Statistical modeling, Optimization (mathematics), Statistical analysis, Computed tomography, Data modeling, Medical imaging, Image segmentation, 3D modeling

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Proceedings Article | 19 March 2014 Paper

The development of a population of 4D pediatric XCAT phantoms for CT imaging research and optimization

Hannah Norris, Yakun Zhang, Jack Frush, Gregory Sturgeon, Anum Minhas, Daniel Tward, J. Tilak Ratnanather, M. Miller, Donald Frush, Ehsan Samei, W. Paul Segars

Proceedings Volume 9033, 90331V (2014) https://doi.org/10.1117/12.2043777

KEYWORDS: Computed tomography, Motion models, 3D modeling, Data modeling, Monte Carlo methods, Image segmentation, Image quality, Detection and tracking algorithms, 3D acquisition, 3D image processing

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Proceedings Article | 3 March 2012 Paper

Series of 4D adult XCAT phantoms for imaging research and dosimetry

Jason Bond, Jack Frush, Sylvia Hon, Chris Eckersley, Cameron Williams, Jianqiao Feng, Daniel Tward, Tilak J. Ratnanather, M. Miller, D. Frush, E. Samei, W. Segars

Proceedings Volume 8313, 83130P (2012) https://doi.org/10.1117/12.911676

KEYWORDS: 3D modeling, Motion models, Computed tomography, Image segmentation, Medical imaging, Monte Carlo methods, Medical research, Imaging devices, Computer simulations, Data modeling

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Proceedings Article | 22 March 2010 Paper

The generalized NEQ and detectability index for tomosynthesis and cone-beam CT: from cascaded systems analysis to human observers

G. Gang, J. Lee, J. Stayman, D. Tward, W. Zbijewski, J. Prince, J. Siewerdsen

Proceedings Volume 7622, 76220Y (2010) https://doi.org/10.1117/12.845462

KEYWORDS: 3D modeling, Systems modeling, Imaging systems, Performance modeling, Optical spheres, 3D image processing, Interference (communication), Sensors, Eye models, Eye

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Purpose: In the early development of new imaging modalities - such as tomosynthesis and cone-beam CT (CBCT) - an accurate predictive model for imaging performance is particularly valuable in identifying the physical factors that govern image quality and guiding system optimization. In this work, a task-based cascaded systems model for detectability index is proposed that describes not only the signal and noise propagation in the 2D (projection) and 3D (reconstruction) imaging chain but also the influence of background anatomical noise. The extent to which generalized detectability index provides a valid metric for imaging performance was assessed through direct comparison to human observer experiments. Methods: Detectability index (d') was generalized to include anatomical background noise in the same manner as the generalized noise-equivalent quanta (NEQ) proposed by Barrett et al. (Proc. SPIE Med. Imaging, Vol. 1090, 1989). Anatomical background noise was measured from a custom phantom designed to present power-law spectral density comparable to various anatomical sites (e.g., breast and lung). Theoretical calculations of d' as a function of the sourcedetector orbital extent (θ_tot) was obtained from a 3D cascaded systems analysis model for tomosynthesis and cone-beam CT (CBCT). Four model observers were considered in the calculation of d': prewhitening (PW), non-prewhitening (NPW), prewhitening with eye filter and internal noise (PWE), and non-prewhitening with eye filter and internal noise (NPWE). Human observer performance was measured from 9AFC tests for a variety of idealized imaging tasks presented within a clutter phantom. Theoretical results (d') were converted to area under the ROC curve (Az) and compared directly to human observer performance as a function of imaging task and orbital extent. Results: Theoretical results demonstrated reasonable correspondence with human observer response for all tasks across the continuum in θ_tot ranging from low-angle tomosynthesis (θ_tot ~10^o) to CBCT (θ_tot ~180^o). Both theoretical and experimental Az were found to increase with acquisition angle, consistent with increased rejection of out-of-plane clutter for larger tomosynthesis angle. Of the four theoretical model observers considered, the prewhitening models tended to overestimate real observer performance, while the non-prewhitening models demonstrated reasonable agreement. Conclusions: Generalized detectability index was shown to provide a meaningful metric for imaging performance, helping to bridge the gap between real observer performance and prevalent Fourier-based metrics based in first principles of spatial-frequency-dependent NEQ and imaging task.

Proceedings Article | 13 March 2009 Paper

Analysis of lung nodule detectability and anatomical clutter in tomosynthesis imaging of the chest

Sungwon Yoon, Jianan Gang, Daniel Tward, Jeffrey Siewerdsen, Rebecca Fahrig

Proceedings Volume 7258, 72581M (2009) https://doi.org/10.1117/12.813836

KEYWORDS: Picosecond phenomena, Lung, Sensors, Imaging systems, 3D acquisition, Reconstruction algorithms, 3D image processing, Chest, Interference (communication), Signal detection

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Tomosynthesis is an imaging technique that has gained renewed interest with recent advancements of flat-panel digital detectors. Because of the wide range of potential applications, a systematic analysis of 3D tomosynthesis imaging systems would contribute to the understanding and development. This paper extends a systematic evaluation of thoracic tomosynthetic imaging performance as a function of imaging parameters, such as the number of projections, tomosynthesis orbital extent, and reconstruction filters. We evaluate lung nodule detectability and anatomical clutter as a function of tomosynthesis orbital extent using anthropomorphic phantoms and a table-top acquisition system. Tomosynthesis coronal slices were reconstructed using the FDK algorithm for cone-beam geometry from 91 projections uniformly distributed over acquisition orbital extents (θ) ranging from 10° to 180°. Visual comparisons of different tomosynthesis reconstructions of a lung nodule show the progressive decrease of anatomical clutter as θ increases. Additionally, three quantitative figures of merit were computed and compared: signal-difference-to-noise ratio (SDNR), anatomical clutter power spectrum (PS), and theoretical detectability index (DI). Lung nodule SDNR increases as θ increases from 0° to 120°. Anatomical clutter PS shows that the clutter magnitude and correlation decrease as θ increases, increasing detectability. Similarly, 2D and 3D DI increase as θ increases in the anatomical dominated exposure ranges. On the other hand, 2D slice DI is lower than the 3D DI for larger θ (e.g. 120°), because of the information loss in the depth direction for 2D slices. In other words, inspecting 3D is better for larger acquisition orbital extents, because the extra information acquired at larger angles cannot be fully recovered from 2D tomosynthesis reconstruction slices. In summary, detectability in tomosynthesis reconstructions for thoracic imaging increases as fixed dose is distributed over a larger acquisition orbital extent (up to 120°).

Proceedings Article | 3 April 2008 Paper

Cascaded systems analysis of the 3D NEQ for cone-beam CT and tomosynthesis

D. Tward, J. Siewerdsen, R. Fahrig, A. Pineda

Proceedings Volume 6913, 69131S (2008) https://doi.org/10.1117/12.772999

KEYWORDS: 3D modeling, 3D metrology, 3D image processing, Sensors, Imaging systems, Modulation transfer functions, Interference (communication), Systems modeling, Stereoscopy, X-rays

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Proceedings Article | 3 April 2008 Paper

Analysis of image noise in 3D cone-beam CT: spatial and Fourier domain approaches under conditions of varying stationarity

Angel Pineda, Jeffrey Siewerdsen, Daniel Tward

Proceedings Volume 6913, 69131Q (2008) https://doi.org/10.1117/12.772966

KEYWORDS: Sensors, Image filtering, Modulation, Optical filters, Imaging systems, Signal detection, Image analysis, X-rays, 3D image processing, Computed tomography

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Proceedings Article | 18 March 2008 Paper

NEQ and task in dual-energy imaging: from cascaded systems analysis to human observer performance

Samuel Richard, Jeffrey Siewerdsen, Daniel Tward

Proceedings Volume 6913, 691311 (2008) https://doi.org/10.1117/12.772772

KEYWORDS: Imaging systems, Modulation transfer functions, Image filtering, Optical spheres, Eye models, Eye, Linear filtering, Electronic filtering, Laser sintering, Systems modeling

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Proceedings Article | 20 March 2007 Paper

Development and implementation of a high-performance cardiac-gated dual-energy imaging system

N. Shkumat, J. Siewerdsen, A. Dhanantwari, D. Williams, S. Richard, D. Tward, N. Paul, J. Yorkston, R. Van Metter

Proceedings Volume 6510, 651006 (2007) https://doi.org/10.1117/12.713680

KEYWORDS: Imaging systems, X-rays, Radiography, Lung, Heart, Diagnostics, Oximeters, Image filtering, Image processing, Sensors

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Showing 5 of 9 publications

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