Dr. Loren W. Nolte Profile

Dr. Loren W. Nolte

Professor of Electrical and Computer Engineering at Duke Univ Pratt School of Engineering

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Publications (9)

SPIE Journal Paper | 13 September 2016

Impact of breast structure on lesion detection in breast tomosynthesis, a simulation study

Nooshin Kiarashi, Loren Nolte, Joseph Lo, W. Paul Segars, Sujata Ghate, Justin Solomon, Ehsan Samei

JMI, Vol. 3, Issue 03, 035504, (September 2016) https://doi.org/10.1117/12.10.1117/1.JMI.3.3.035504

KEYWORDS: Breast, Tissues, Sensors, Data modeling, Performance modeling, Human subjects, Monte Carlo methods, Computer simulations, Imaging systems, Mathematical modeling

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This study aims to characterize the effect of background tissue density and heterogeneity on the detection of irregular masses in breast tomosynthesis, while demonstrating the capability of the sophisticated tools that can be used in the design, implementation, and performance analysis of virtual clinical trials (VCTs). Twenty breast phantoms from the extended cardiac-torso (XCAT) family, generated based on dedicated breast computed tomography of human subjects, were used to extract a total of 2173 volumes of interest (VOIs) from simulated tomosynthesis images. Five different lesions, modeled after human subject tomosynthesis images, were embedded in the breasts and combined with the lesion absent condition yielded a total of 6×2173 VOIs. Effects of background tissue density and heterogeneity on the detection of the lesions were studied by implementing a composite hypothesis signal detection paradigm with location known exactly, lesion known exactly or statistically, and background known statistically. Using the area under the receiver operating characteristic curve, detection performance deteriorated as density was increased, yielding findings consistent with clinical studies. A human observer study was performed on a subset of the simulated tomosynthesis images, confirming the detection performance trends with respect to density and serving as a validation of the implemented detector. Performance of the implemented detector varied substantially across the 20 breasts. Furthermore, background tissue density and heterogeneity affected the log-likelihood ratio test statistic differently under lesion absent and lesion present conditions. Therefore, considering background tissue variability in tissue models can change the outcomes of a VCT and is hence of crucial importance. The XCAT breast phantoms have the potential to address this concern by offering realistic modeling of background tissue variability based on a wide range of human subjects, comprising various breast shapes, sizes, and densities.

Proceedings Article | 18 March 2015 Paper

The impact of breast structure on lesion detection in breast tomosynthesis

Nooshin Kiarashi, Loren Nolte, Joseph Lo, William Segars, Sujata Ghate, Ehsan Samei

Proceedings Volume 9412, 941229 (2015) https://doi.org/10.1117/12.2082473

KEYWORDS: Breast, Tissues, Sensors, Human subjects, 3D modeling, Data modeling, Clinical trials, Signal detection, Digital breast tomosynthesis, Composites

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Proceedings Article | 19 March 2013 Paper

Development of matched virtual and physical breast phantoms based on patient data

Nooshin Kiarashi, Gregory Sturgeon, Loren Nolte, Joseph Lo, James Dobbins, William Segars, Ehsan Samei

Proceedings Volume 8668, 866805 (2013) https://doi.org/10.1117/12.2008406

KEYWORDS: Breast, Tissues, 3D modeling, Tissue optics, Statistical analysis, Imaging systems, Mathematical modeling, Signal attenuation, X-ray imaging, X-rays

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Proceedings Article | 9 March 2012 Paper

Development of a dynamic 4D anthropomorphic breast phantom for contrast-based breast imaging

Nooshin Kiarashi, Yuan Lin, William Segars, Sujata Ghate, Lynda Ikejimba, Baiyu Chen, Joseph Lo, James Dobbins, Loren Nolte, Ehsan Samei

Proceedings Volume 8313, 83130C (2012) https://doi.org/10.1117/12.913332

KEYWORDS: Breast, Tissues, Mathematical modeling, Breast imaging, Imaging systems, Mammography, Reconstruction algorithms, Blood, Signal attenuation, Digital mammography

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Proceedings Article | 17 March 2006 Paper

The effect of data set size on computer-aided diagnosis of breast cancer: comparing decision fusion to a linear discriminant

Jonathan Jesneck, Loren Nolte, Jay Baker, Joseph Lo

Proceedings Volume 6146, 614616 (2006) https://doi.org/10.1117/12.655235

KEYWORDS: Data fusion, Data modeling, Computer aided diagnosis and therapy, Breast cancer, Solid modeling, Binary data, Tumor growth modeling, Statistical analysis, Feature extraction, Mammography

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Proceedings Article | 11 September 2003 Paper

Optimal multisensor decision fusion of mine detection algorithms

Yuwei Liao, Loren Nolte, Leslie Collins

Proceedings Volume 5089, (2003) https://doi.org/10.1117/12.486834

KEYWORDS: Sensors, General packet radio service, Data fusion, Detection and tracking algorithms, Land mines, Algorithm development, Ground penetrating radar, Metals, Signal detection, Statistical analysis

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Proceedings Article | 2 August 1999 Paper

Bayesian signal detection for multiple aspect targets with an uncertain look angle

Jennifer Rasimas, Stacy Tantum, Loren Nolte

Proceedings Volume 3710, (1999) https://doi.org/10.1117/12.357024

KEYWORDS: Signal detection, Signal to noise ratio, Target detection, Interference (communication), Signal processing, Sensors, Acoustics, Data centers, Detection theory, Receivers

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Proceedings Article | 16 April 1996 Paper

Hierarchical Markov random-field modeling for texture classification in chest radiographs

Rene Vargas-Voracek, Carey Floyd, Loren Nolte, Page McAdams

Proceedings Volume 2710, (1996) https://doi.org/10.1117/12.237971

KEYWORDS: Image classification, Lung, Bone, Chest imaging, Image analysis, Image processing, Radiology, Volume rendering, Algorithms, Electrical engineering

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Proceedings Article | 1 November 1991 Paper

Detection of unresolved target tracks in infrared imagery

Sarah Rajala, Loren Nolte, James Aanstoos

Proceedings Volume 1606, (1991) https://doi.org/10.1117/12.50334

KEYWORDS: Detection and tracking algorithms, Target detection, Image processing, 3D image processing, 3D acquisition, Signal to noise ratio, Error analysis, Detection theory, Radon transform, Visual communications

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Showing 5 of 9 publications

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