Dr. Amy C. Sharma Profile

Dr. Amy C. Sharma

at Duke Univ

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Author

Publications (6)

Proceedings Article | 16 May 2011 Paper

Detecting gait alterations due to concussion impairment with radar using information-theoretic techniques

Jennifer Palmer, Kristin Bing, Amy Sharma, Eugene Greneker, Teresa Selee

Proceedings Volume 8029, 80290U (2011) https://doi.org/10.1117/12.883278

KEYWORDS: Goggles, Gait analysis, Information technology, Radar, Traumatic brain injury, Matrices, Statistical analysis, Visualization, Analytical research, Blood

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Proceedings Article | 16 March 2007 Paper

Elemental spectrum of a mouse obtained via neutron stimulation

Amy Sharma, Georgia Tourassi, Anuj Kapadia, Alexander Crowell, Matthew Kiser, Anthony Hutcheson, Brian Harrawood, Calvin Howell, Carey Floyd

Proceedings Volume 6510, 65100K (2007) https://doi.org/10.1117/12.713731

KEYWORDS: Chemical elements, Imaging spectroscopy, In vivo imaging, Germanium, Sensors, Gamma radiation, Tomography, Calcium, Gadolinium, Spectroscopy

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Proceedings Article | 2 March 2006 Paper

Breast cancer diagnosis using neutron stimulated emission computed tomography: dose and count requirements

Carey Floyd Jr., Janelle Bender, Brian Harrawood, Amy Sharma, Anuj Kapadia, Georgia Tourassi, Joseph Lo, Calvin Howell

Proceedings Volume 6142, 61421O (2006) https://doi.org/10.1117/12.656045

KEYWORDS: Breast, Tissues, Bromine, Zinc, Breast cancer, Cesium, Rubidium, Mammography, Cobalt, Tumor growth modeling

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Proceedings Article | 2 March 2006 Paper

Rotating slat collimator design for high-energy near-field imaging

Amy Sharma, Carey Floyd, Brian Harrawood, Georgia Tourassi, Anuj Kapadia, Janelle Bender, Joseph Lo, Calvin Howell

Proceedings Volume 6142, 614217 (2006) https://doi.org/10.1117/12.653929

KEYWORDS: Collimators, Sensors, Spectroscopy, Reconstruction algorithms, Near field, Imaging spectroscopy, Gamma radiation, Modulation, MATLAB, Solar energy

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Certain elements (such as Fe, Cu, Zn, etc.) are vital to the body and an imbalance of such elements can either be a symptom or cause of certain pathologies. Neutron Stimulated Emission Computed Tomography (NSECT) is a spectroscopic imaging technique whereby the body is illuminated via a beam of neutrons causing elemental nuclei to become excited and emit characteristic gamma radiation. Acquiring the gamma energy spectra in a tomographic geometry allows reconstruction of elemental concentration images. Previously we have demonstrated the feasibility of NSECT using first generation CT approaches; while successful, the approach does not scale well and has limited resolution. Additionally, current gamma cameras operate in an energy range too low for NSECT imaging. However, the orbiting Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) captures and images gamma rays over the high-energy range equivalent to NSECT's (3 keV to 17 MeV) by utilizing Collimator-based Fourier transform imaging. A High Purity Germanium (HPGe) detector counts the number of energy events per unit of time, providing spectroscopic data. While a pair of rotating collimators placed in front of the detector modulates the number of gamma events, providing spatial information. Knowledge of the number of energy events at each discrete collimator angle allows for 2D image reconstruction. This method has proven successful at a focus of infinity in the RHESSI application. Our goal is to achieve similar results at a reasonable near-field focus. Here we describe the results of our simulations to implement a rotating modulation collimator (RMC) gamma imager for use in NSECT using simulations in Matlab. To determine feasible collimator setups and the stability of the inverse problem a Matlab environment was created that uses the geometry of the system to generate 1D observation data from 2D images and then to reconstruct 2D images using the MLEM algorithm. Reasonable collimator geometries were determined, successful reconstruction was achieved and the inverse problem was found to be stable.

Proceedings Article | 2 March 2006 Paper

The effect of detector resolution for quantitative analysis of neutron stimulated emission computed tomography

Janelle Bender, Carey Floyd, Brian Harrawood, Anuj Kapadia, Amy Sharma, Jonathan Jesneck

Proceedings Volume 6142, 61424Z (2006) https://doi.org/10.1117/12.652812

KEYWORDS: Sensors, Breast, Tissues, Monte Carlo methods, Tumor growth modeling, Germanium, Computed tomography, Data modeling, Zinc, Scintillators

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Proceedings Article | 12 April 2005 Paper

Image processing and data acquisition optimization for acoustic radiation force impulse imaging of in vivo breast masses

Amy Sharma, Gregg Trahey, Kristin Frinkley, Mary Scott Soo, Mark Palmeri, Kathryn Nightingale

Proceedings Volume 5750, (2005) https://doi.org/10.1117/12.593473

KEYWORDS: Tissues, In vivo imaging, Acoustics, Breast, Data acquisition, Edge detection, Image quality, Algorithm development, Transducers, Image processing

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Acoustic Radiation Force Impulse (ARFI) imaging utilizes brief, high-energy acoustic pulses to excite tissue and ultrasonic correlation based tracking methods to monitor the resulting tissue displacement, which reflects the relative mechanical properties of tissue (i.e. stiffer tissue displaces less). ARFI image contrast is optimized utilizing tightly focused radiation force excitations at multiple axial and lateral locations throughout a 2D field of view. In an ongoing, IRB approved, clinical study, suspicious breast lesions are interrogated in vivo via multi-focal-zone ARFI prior to undergoing core biopsy. A Siemens SONOLINE Antares (TM) scanner and VF10-5 probe were configured to acquire ARFI data from multiple focal-zones and lateral locations. Data was acquired in real-time, and processed off-line. Processing included: filtering, parametric data analysis, normalization and combination of the multiple focal-zone data, and automatic edge detection. ARFI sequences were designed with varying pushing pulse frequencies and intensities. Contrast to noise ratio was evaluated in a tissue mimicking phantom for lesions at different depths using the different pushing pulse sequences. For shallower lesions (depth=10mm), CNR was higher than for deeper lesions, and did not vary appreciably for the different push sequences. For deeper lesions (depth=20mm), CNR increased with increasing push pulse intensity and decreasing push pulse frequency. With the pushing pulse transmit intensity calibrated (in a homogeneous phantom) to achieve uniform displacement at all axial depths, in vivo results yielded poor SNR at depth and did not achieve overall uniform displacement. In vivo, image quality improved with increasing push pulse intensity. To date, 27 masses have been interrogated using multi-focal-zone ARFI and overall good structural agreement exists between B-mode and ARFI images. Normalization and blending facilitate image generation from ARFI interrogation using different intensities at different focal depths.

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