Prof. Gene Gindi Profile

Prof. Gene Gindi

at Stony Brook Univ

SPIE Involvement:

Author

Publications (17)

Proceedings Article | 19 March 2014 Paper

A simple scatter correction method for dual energy contrast-enhanced digital breast tomosynthesis

Yihuan Lu, Beverly Lau, Yue-Houng Hu, Wei Zhao, Gene Gindi

Proceedings Volume 9033, 903344 (2014) https://doi.org/10.1117/12.2043190

KEYWORDS: Iodine, Breast, Digital breast tomosynthesis, Sensors, Mammography, Dual energy imaging, Tumors, Lead, Data acquisition, Reconstruction algorithms

Read Abstract +

Proceedings Article | 6 March 2013 Paper

Impact of subtraction and reconstruction strategies on dual-energy contrast enhanced breast tomosynthesis with interleaved acquisition

Lin Chen, Yihuan Lu, Yue-Houng Hu, Wei Zhao, Gene Gindi

Proceedings Volume 8668, 86685O (2013) https://doi.org/10.1117/12.2007960

KEYWORDS: Digital breast tomosynthesis, Reconstruction algorithms, Remote sensing, Breast, Data acquisition, Sensors, X-rays, Image quality, Iodine, Image contrast enhancement

Read Abstract +

Proceedings Article | 24 February 2010 Paper

Rapid performance evaluation for ideal FROC and AFROC observers

Bin Liu, Parmeshwar Khurd, Gene Gindi

Proceedings Volume 7627, 76270V (2010) https://doi.org/10.1117/12.844412

KEYWORDS: Signal detection, Radon, Tolerancing, Medical imaging, Interference (communication), Lawrencium, Signal to noise ratio, Imaging systems, Image enhancement, Retina

Read Abstract +

Proceedings Article | 13 March 2009 Paper

On ideal AFROC and FROC observers

Parmeshwar Khurd, Bin Liu, Gene Gindi

Proceedings Volume 7263, 72630S (2009) https://doi.org/10.1117/12.811183

KEYWORDS: Radon, Signal detection, Computer aided diagnosis and therapy, Medical imaging, Multidimensional signal processing, Tolerancing, Receivers, Imaging systems, Computer aided design, Image processing

Read Abstract +

Proceedings Article | 6 March 2008 Paper

SPECT image system optimization using ideal observer for detection and localization

Lili Zhou, Gene Gindi

Proceedings Volume 6917, 69171D (2008) https://doi.org/10.1117/12.770676

KEYWORDS: Collimators, Imaging systems, Tolerancing, Signal detection, Single photon emission computed tomography, Tomography, Signal attenuation, Data modeling, Sensors, Image resolution

Read Abstract +

Proceedings Article | 2 March 2006 Paper

Low-contrast lesion detection in tomosynthetic breast imaging using a realistic breast phantom

Lili Zhou, Jorge Oldan, Paul Fisher, Gene Gindi

Proceedings Volume 6142, 61425A (2006) https://doi.org/10.1117/12.652343

KEYWORDS: Breast, Mammography, Reconstruction algorithms, Expectation maximization algorithms, 3D modeling, Sensors, Tissues, Nipple, Signal attenuation, Breast imaging

Read Abstract +

Tomosynthesis mammography is a potentially valuable technique for detection of breast cancer. In this simulation study, we investigate the efficacy of three different tomographic reconstruction methods, EM, SART and Backprojection, in the context of an especially difficult mammographic detection task. The task is the detection of a very low-contrast mass embedded in very dense fibro-glandular tissue - a clinically useful task for which tomosynthesis may be well suited. The project uses an anatomically realistic 3D digital breast phantom whose normal anatomic variability limits lesion conspicuity. In order to capture anatomical object variability, we generate an ensemble of phantoms, each of which comprises random instances of various breast structures. We construct medium-sized 3D breast phantoms which model random instances of ductal structures, fibrous connective tissue, Cooper's ligaments and power law structural noise for small scale object variability. Random instances of 7-8 mm irregular masses are generated by a 3D random walk algorithm and placed in very dense fibro-glandular tissue. Several other components of the breast phantom are held fixed, i.e. not randomly generated. These include the fixed breast shape and size, nipple structure, fixed lesion location, and a pectoralis muscle. We collect low-dose data using an isocentric tomosynthetic geometry at 11 angles over 50 degrees and add Poisson noise. The data is reconstructed using the three algorithms. Reconstructed slices through the center of the lesion are presented to human observers in a 2AFC (two-alternative-forced-choice) test that measures detectability by computing AUC (area under the ROC curve). The data collected in each simulation includes two sources of variability, that due to the anatomical variability of the phantom and that due to the Poisson data noise. We found that for this difficult task that the AUC value for EM (0.89) was greater than that for SART (0.83) and Backprojection (0.66).

Proceedings Article | 6 April 2005 Paper

Decision strategies maximizing the area under the LROC curve

Parmeshwar Khurd, Gene Gindi

Proceedings Volume 5749, (2005) https://doi.org/10.1117/12.595915

KEYWORDS: Tolerancing, Signal detection, Tumors, Imaging systems, Medical imaging, Mammography, Data modeling, Image processing, Data processing, Performance modeling

Read Abstract +

Proceedings Article | 4 May 2004 Paper

LROC model observers for emission tomographic reconstruction

Parmeshwar Khurd, Gene Gindi

Proceedings Volume 5372, (2004) https://doi.org/10.1117/12.536442

KEYWORDS: Lab on a chip, Signal detection, Sensors, Reconstruction algorithms, Tomography, Monte Carlo methods, Detection theory, Prototyping, Performance modeling, Data modeling

Read Abstract +

SPIE Journal Paper | 1 January 2003

Bayesian image reconstruction for transmission tomography using deterministic annealing

Ing-Tsung Hsiao, Anand Rangarajan, Gene Gindi

JEI, Vol. 12, Issue 01, (January 2003) https://doi.org/10.1117/12.10.1117/1.1526103

KEYWORDS: Signal attenuation, Annealing, Reconstruction algorithms, Tomography, Positron emission tomography, Single photon emission computed tomography, Model-based design, Lung, Tissues, Image restoration

Proceedings Article | 9 May 2002 Paper

Provably convergent OSEM-like reconstruction algorithm for emission tomography

Ing-Tsung Hsiao, Anand Rangarajan, Gene Gindi

Proceedings Volume 4684, (2002) https://doi.org/10.1117/12.467144

KEYWORDS: Reconstruction algorithms, Expectation maximization algorithms, Tomography, Algorithm development, Positron emission tomography, Single photon emission computed tomography, CT reconstruction, Medical imaging, Chemical elements, Optimization (mathematics)

Read Abstract +

Proceedings Article | 3 July 2001 Paper

Bayesian image reconstruction for transmission tomography using mixture model priors and deterministic annealing algorithms

Ing-Tsung Hsiao, Anand Rangarajan, Gene Gindi

Proceedings Volume 4322, (2001) https://doi.org/10.1117/12.431169

KEYWORDS: Reconstruction algorithms, Signal attenuation, Tomography, Annealing, Expectation maximization algorithms, Tissues, Lung, Positron emission tomography, Image restoration, Bone

Read Abstract +

Proceedings Article | 28 May 1999 Paper

Using a digital anatomical phantom to optimize an imaging system

Stephan Faris, Donald Wilson, Harrison Barrett, Doug Dougherty, Gene Gindi, Ing-Tsung Hsiao

Proceedings Volume 3659, (1999) https://doi.org/10.1117/12.349565

KEYWORDS: Tumors, Cameras, Imaging systems, Brain, Semiconductors, Single photon emission computed tomography, Fractal analysis, Scintillators, Computer simulations, Signal detection

Read Abstract +

Proceedings Article | 31 October 1997 Paper

Quantitative effects of using thin-plate priors in Bayesian SPECT reconstruction

Soo-Jin Lee, Ing-Tsung Hsiao, Gene Gindi

Proceedings Volume 3170, (1997) https://doi.org/10.1117/12.292826

KEYWORDS: Single photon emission computed tomography, Data modeling, Yield improvement, Sensors, Performance modeling, Optimization (mathematics), Expectation maximization algorithms

Read Abstract +

Proceedings Article | 25 April 1997 Paper

Autoradiographic-based phantoms for emission tomography

Gene Gindi, Doug Dougherty, Ing-Tsung Hsiao, Anand Rangarajan

Proceedings Volume 3034, (1997) https://doi.org/10.1117/12.274126

KEYWORDS: Brain, Autoregressive models, Single photon emission computed tomography, Tissues, Capillaries, Data modeling, Neuroimaging, Monte Carlo methods, Imaging systems, Radioisotopes

Read Abstract +

Proceedings Article | 10 October 1994 Paper

Segmentation using atlas-guided deformable contours

Chun Chang, Anand Rangarajan, Gene Gindi

Proceedings Volume 2353, (1994) https://doi.org/10.1117/12.188893

KEYWORDS: Image segmentation, Image processing algorithms and systems, Visual process modeling, Machine vision, Computer vision technology, Condition numbers, Binary data, Magnetism, Magnetic resonance imaging, Medical imaging

Read Abstract +

Proceedings Article | 29 July 1993 Paper

Atlas-guided segmentation of brain images via optimizing neural networks

Gene Gindi, Anand Rangarajan, I. Zubal

Proceedings Volume 1905, (1993) https://doi.org/10.1117/12.148668

KEYWORDS: Image segmentation, Brain, Neuroimaging, Magnetic resonance imaging, Neural networks, Data modeling, Magnetism, Image registration, Binary data, Radiology

Read Abstract +

Proceedings Article | 16 September 1992 Paper

Neural network approach to object recognition and image partitioning within a resolution hierarchy

Joachim Utans, Gene Gindi

Proceedings Volume 1709, (1992) https://doi.org/10.1117/12.140000

KEYWORDS: Data modeling, Object recognition, Neural networks, Artificial neural networks, Visual process modeling, Neurons, Image resolution, Image segmentation, Complex systems, Pattern recognition

Read Abstract +

Showing 5 of 17 publications

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years