Dr. David A. Langan Profile

Dr. David A. Langan

at GE Research

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Author

Publications (12)

Proceedings Article | 18 March 2015 Paper

Interventional C-arm tomosynthesis for vascular imaging: initial results

David Langan, Bernhard Claus, Omar Al Assad, Yves Trousset, Cyril Riddell, Gregoire Avignon, Stephen Solomon, Hao Lai, Xin Wang

Proceedings Volume 9412, 94125N (2015) https://doi.org/10.1117/12.2081195

KEYWORDS: Vascular imaging, 3D image processing, Calibration, 3D acquisition, 3D vision, Angiography, Stereoscopy, Sensors, Head, Arteries

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Proceedings Article | 18 March 2015 Paper

Circular tomosynthesis for neuro perfusion imaging on an interventional C-arm

Bernhard Claus, David Langan, Omar Al Assad, Xin Wang

Proceedings Volume 9412, 94122A (2015) https://doi.org/10.1117/12.2082695

KEYWORDS: Reconstruction algorithms, Data modeling, Data acquisition, Temporal resolution, Computed tomography, Image quality, Physics, Imaging systems, Tomography, Signal attenuation

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Proceedings Article | 23 March 2010 Paper

Effective atomic number accuracy for kidney stone characterization using spectral CT

M. Joshi, D. Langan, D. Sahani, A. Kambadakone, S. Aluri, K. Procknow, X. Wu, R. Bhotika, D. Okerlund, N. Kulkarni, D. Xu

Proceedings Volume 7622, 76223K (2010) https://doi.org/10.1117/12.844372

KEYWORDS: Renal calculi, Signal attenuation, Calcium, Dual energy imaging, Computed tomography, Kidney, X-ray computed tomography, Imaging spectroscopy, Spine, Medicine

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Proceedings Article | 22 March 2010 Paper

Initial use of fast switched dual energy CT for coronary artery disease

William Pavlicek, Prasad Panse, Amy Hara, Thomas Boltz, Robert Paden, Didem Yamak, Paul Licato, Naveen Chandra, Darin Okerlund, Sandeep Dutta, Rahul Bhotika, David Langan

Proceedings Volume 7622, 76221V (2010) https://doi.org/10.1117/12.844859

KEYWORDS: Dual energy imaging, Calcium, Iodine, Visualization, Arteries, Tissues, Heart, Signal attenuation, X-rays, X-ray imaging

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Proceedings Article | 9 March 2010 Paper

Automated liver lesion characterization using fast kVp switching dual energy computed tomography imaging

Alberto Santamaria-Pang, Sandeep Dutta, Sokratis Makrogiannis, Amy Hara, William Pavlicek, Alvin Silva, Brian Thomsen, Scott Robertson, Darin Okerlund, David Langan, Rahul Bhotika

Proceedings Volume 7624, 76240V (2010) https://doi.org/10.1117/12.844059

KEYWORDS: Computed tomography, Dual energy imaging, Liver, Image classification, Switching, Signal attenuation, Tumors, Imaging spectroscopy, Medicine, X-ray computed tomography

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Hypodense metastases are not always completely distinguishable from benign cysts in the liver using conventional Computed Tomography (CT) imaging, since the two lesion types present with overlapping intensity distributions due to similar composition as well as other factors including beam hardening and patient motion. This problem is extremely challenging for small lesions with diameter less than 1 cm. To accurately characterize such lesions, multiple follow-up CT scans or additional Positron Emission Tomography or Magnetic Resonance Imaging exam are often conducted, and in some cases a biopsy may be required after the initial CT finding. Gemstone Spectral Imaging (GSI) with fast kVp switching enables projection-based material decomposition, offering the opportunity to discriminate tissue types based on their energy-sensitive material attenuation and density. GSI can be used to obtain monochromatic images where beam hardening is reduced or eliminated and the images come inherently pre-registered due to the fast kVp switching acquisition. We present a supervised learning method for discriminating between cysts and hypodense liver metastases using these monochromatic images. Intensity-based statistical features extracted from voxels inside the lesion are used to train optimal linear and nonlinear classifiers. Our algorithm only requires a region of interest within the lesion in order to compute relevant features and perform classification, thus eliminating the need for an accurate segmentation of the lesion. We report classifier performance using M-fold cross-validation on a large lesion database with radiologist-provided lesion location and labels as the reference standard. Our results demonstrate that (a) classification using a single projection-based spectral CT image, i.e., a monochromatic image at a specified keV, outperforms classification using an image-based dual energy CT pair, i.e., low and high kVp images derived from the same fast kVp acquisition and (b) classification using monochromatic images can achieve very high accuracy in separating benign liver cysts and metastases, especially for small lesions.

Proceedings Article | 14 March 2009 Paper

Monochromatic CT image representation via fast switching dual kVp

Xiaoye Wu, David Langan, Dan Xu, Thomas Benson, Jed Pack, Andrea Schmitz, Eric Tkaczyk, Jaynne Leverentz, Paul Licato

Proceedings Volume 7258, 725845 (2009) https://doi.org/10.1117/12.811698

KEYWORDS: X-rays, X-ray computed tomography, X-ray imaging, Signal attenuation, Photons, Medical imaging, Switching, Fast packet switching, Sensors, Dual energy imaging

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Proceedings Article | 14 March 2009 Paper

Dual energy CT via fast kVp switching spectrum estimation

Dan Xu, David Langan, Xiaoye Wu, Jed Pack, Thomas Benson, J. Eric Tkaczky, Andrea Schmitz

Proceedings Volume 7258, 72583T (2009) https://doi.org/10.1117/12.811650

KEYWORDS: Iodine, Switching, Dual energy imaging, Signal attenuation, Sensors, X-rays, Clocks, Fast packet switching, Image quality, Computed tomography

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Proceedings Article | 14 March 2009 Paper

Fast kVp switching CT imaging of a dynamic cardiac phantom

Jed Pack, David Langan, Xiaoye Wu, Dan Xu, Thomas Benson, Andrea Schmitz, J. Eric Tkaczyk, William Pavlicek, Thomas Boltz, Robert Payden, Jaynne Leverentz, Paul Licato

Proceedings Volume 7258, 725843 (2009) https://doi.org/10.1117/12.811641

KEYWORDS: Heart, Dual energy imaging, Switching, Computed tomography, Data acquisition, Iodine, Electrocardiography, Arteries, Cardiac imaging, Sensors

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Proceedings Article | 11 March 2009 Paper

Quantization of liver tissue in dual kVp computed tomography using linear discriminant analysis

J. Eric Tkaczyk, David Langan, Xiaoye Wu, Daniel Xu, Thomas Benson, Jed Pack, Andrea Schmitz, Amy Hara, William Palicek, Paul Licato, Jaynne Leverentz

Proceedings Volume 7258, 72580G (2009) https://doi.org/10.1117/12.811374

KEYWORDS: Tissues, Iodine, Liver, Dual energy imaging, Signal attenuation, X-ray computed tomography, X-rays, Calibration, Computed tomography, Data modeling

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Proceedings Article | 2 March 2006 Paper

An iterative algorithm for soft tissue reconstruction from truncated flat panel projections

D. Langan, B. Claus, P. Edic, R. Vaillant, B. De Man, S. Basu, M. Iatrou

Proceedings Volume 6142, 614224 (2006) https://doi.org/10.1117/12.652295

KEYWORDS: Reconstruction algorithms, Heart, Imaging systems, Tissues, Sensors, Stereoscopy, X-ray computed tomography, 3D image processing, Image quality, X-rays

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Proceedings Article | 6 July 1994 Paper

Performance results of the bi-level multiple hypothesis tracking (MHT) algorithm for two crossing targets in a high-clutter environment

David Chan, David Langan

Proceedings Volume 2235, (1994) https://doi.org/10.1117/12.179067

KEYWORDS: Detection and tracking algorithms, Palladium, Target detection, Monte Carlo methods, Algorithm development, Computer simulations, Filtering (signal processing), Infrared search and track, Electronic filtering, Surveillance systems

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Proceedings Article | 22 October 1993 Paper

Tracking in a high-clutter environment: simulation results characterizing a bi-level MHT algorithm

David Chan, Daniel Harrison, David Langan

Proceedings Volume 1954, (1993) https://doi.org/10.1117/12.157805

KEYWORDS: Detection and tracking algorithms, Target detection, Monte Carlo methods, Signal to noise ratio, Infrared search and track, Computer simulations, Filtering (signal processing), Palladium, Electronic filtering, Algorithms

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Showing 5 of 12 publications

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