Dr. William J. Ryder Profile

Dr. William J. Ryder

at Univ of Sydney

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Publications (7)

Proceedings Article | 24 March 2016 Paper

Predicting radiologists' true and false positive decisions in reading mammograms by using gaze parameters and image-based features

Ziba Gandomkar, Kevin Tay, Will Ryder, Patrick Brennan, Claudia Mello-Thoms

Proceedings Volume 9787, 978715 (2016) https://doi.org/10.1117/12.2217704

KEYWORDS: Mammography, Eye, Optical tracking, Breast, Visualization, Biopsy, Cancer, Image segmentation, Feature extraction, Tissues, Image filtering, Error analysis, Medical imaging

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Proceedings Article | 17 March 2015 Paper

iDensity: an automatic Gabor filter-based algorithm for breast density assessment

Ziba Gamdonkar, Kevin Tay, Will Ryder, Patrick Brennan, Claudia Mello-Thoms

Proceedings Volume 9416, 941607 (2015) https://doi.org/10.1117/12.2083149

KEYWORDS: Image filtering, Mammography, Digital filtering, Gaussian filters, Breast, Filtering (signal processing), Feature extraction, Digital mammography, Databases, Image classification

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Proceedings Article | 19 March 2014 Paper

Improved attenuation correction for freely moving animal brain PET studies using a virtual scanner geometry

Georgios Angelis, William Ryder, Andre Kyme, Roger Fulton, Steven Meikle

Proceedings Volume 9033, 90334I (2014) https://doi.org/10.1117/12.2043962

KEYWORDS: Scanners, Signal attenuation, Head, Positron emission tomography, Brain, Neuroimaging, Data acquisition, Optical tracking, Photons, Brain imaging

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Proceedings Article | 19 March 2014 Paper

List-mode PET image reconstruction for motion correction using the Intel XEON PHI co-processor

W. Ryder, G. Angelis, R. Bashar, J. Gillam, R. Fulton, S. Meikle

Proceedings Volume 9033, 90335B (2014) https://doi.org/10.1117/12.2043403

KEYWORDS: Image restoration, Reconstruction algorithms, Positron emission tomography, Computing systems, 3D image processing, Algorithm development, Projection systems, Graphics processing units, C++, Physics

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List-mode image reconstruction with motion correction is computationally expensive, as it requires projection of hundreds of millions of rays through a 3D array. To decrease reconstruction time it is possible to use symmetric multiprocessing computers or graphics processing units. The former can have high financial costs, while the latter can require refactoring of algorithms. The Xeon Phi is a new co-processor card with a Many Integrated Core architecture that can run 4 multiple-instruction, multiple data threads per core with each thread having a 512-bit single instruction, multiple data vector register. Thus, it is possible to run in the region of 220 threads simultaneously. The aim of this study was to investigate whether the Xeon Phi co-processor card is a viable alternative to an x86 Linux server for accelerating List-mode PET image reconstruction for motion correction. An existing list-mode image reconstruction algorithm with motion correction was ported to run on the Xeon Phi coprocessor with the multi-threading implemented using pthreads. There were no differences between images reconstructed using the Phi co-processor card and images reconstructed using the same algorithm run on a Linux server. However, it was found that the reconstruction runtimes were 3 times greater for the Phi than the server. A new version of the image reconstruction algorithm was developed in C++ using OpenMP for mutli-threading and the Phi runtimes decreased to 1.67 times that of the host Linux server. Data transfer from the host to co-processor card was found to be a rate-limiting step; this needs to be carefully considered in order to maximize runtime speeds. When considering the purchase price of a Linux workstation with Xeon Phi co-processor card and top of the range Linux server, the former is a cost-effective computation resource for list-mode image reconstruction. A multi-Phi workstation could be a viable alternative to cluster computers at a lower cost for medical imaging applications.

Proceedings Article | 23 March 2010 Paper

Simulation of low dose positron emission mammography scanner for global breast health applications

W. Ryder, I. Wienberg, P. Stepanov, A. Reznik, M. Urdaneta, E. Anashkin, M. Masoomi, A Rozenfeld

Proceedings Volume 7622, 762249 (2010) https://doi.org/10.1117/12.844017

KEYWORDS: Sensors, Crystals, Monte Carlo methods, Mammography, Scanners, Breast, Absorption, Imaging systems, Cameras, Breast imaging

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Proceedings Article | 18 March 2008 Paper

Generic iterative reconstruction of multi-pinhole SPECT

William Ryder, Matthew Brennan, Albert Sinusas, Yi-Hwa Liu

Proceedings Volume 6913, 69132M (2008) https://doi.org/10.1117/12.769519

KEYWORDS: Sensors, Collimators, Single photon emission computed tomography, Reconstruction algorithms, Expectation maximization algorithms, Image processing, Monte Carlo methods, Heart, Signal to noise ratio, Spatial resolution

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Proceedings Article | 17 March 2008 Paper

Hotspot quantification of myocardial focal tracer uptake from molecular targeted SPECT/CT images: experimental validation

Yi-Hwa Liu, Zakir Sahul, Christopher Weyman, William Ryder, Donald Dione, Lawrence Dobrucki, Choukri Mekkaoui, Matthew Brennan, Xiaoyue Hu, Christi Hawley, Albert Sinusas

Proceedings Volume 6915, 69150N (2008) https://doi.org/10.1117/12.768985

KEYWORDS: Single photon emission computed tomography, Image segmentation, Signal attenuation, Error analysis, X-ray computed tomography, Computed tomography, In vivo imaging, Heart, Medicine, X-ray imaging

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We have developed a new single photon emission computerized tomography (SPECT) hotspot quantification method incorporating extra cardiac activity correction and hotspot normal limit estimation. The method was validated for estimation accuracy of myocardial tracer focal uptake in a chronic canine model of myocardial infarction (MI). Dogs (n = 4) at 2 weeks post MI were injected with Tl-201 and a Tc-99m-labeled hotspot tracer targeted at matrix metalloproteinases (MMPs). An external point source filled with Tc-99m was used for a reference of absolute radioactivity. Dual-isotope (Tc-99m/Tl-201) SPECT images were acquired simultaneously followed by an X-ray CT acquisition. Dogs were sacrificed after imaging for myocardial gamma well counting. Images were reconstructed with CT-based attenuation correction (AC) and without AC (NAC) and were quantified using our quantification method. Normal limits for myocardial hotspot uptake were estimated based on 3 different schemes: maximum entropy, meansquared-error minimization (MSEM) and global minimization. Absolute myocardial hotspot uptake was quantified from SPECT images using the normal limits and compared with well-counted radioactivity on a segment-by-segment basis (n = 12 segments/dog). Radioactivity was expressed as % injected dose (%ID). There was an excellent correlation (r = 0.78-0.92) between the estimated activity (%ID) derived using the SPECT quantitative approach and well-counting, independent of AC. However, SPECT quantification without AC resulted in the significant underestimation of radioactivity. Quantification using SPECT with AC and the MSEM normal limit yielded the best results compared with well-counting. In conclusion, focal myocardial "hotspot" uptake of a targeted radiotracer can be accurately quantified in vivo using a method that incorporates SPECT imaging with AC, an external reference, background scatter compensation, and a suitable normal limit. This hybrid SPECT/CT approach allows for the serial non-invasive quantitative evaluation of molecular targeted tracers in the heart.

Showing 5 of 7 publications

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