Mr. Darin Okerlund Profile

Darin Okerlund

Manager, CT Advanced Applications Engineering at GE Healthcare

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Publications (11)

Proceedings Article | 18 October 2022 Open Access

A five-dimensional cardiac CT model for generating virtual CT projections for user-defined bolus dynamics and ECG profiles

Eri Haneda, Bernhard Claus, Jed Pack, Darin Okerlund, Albert Hsiao, Elliot McVeigh, Bruno De Man

Proceedings Volume 12304, 1230414 (2022) https://doi.org/10.1117/12.2646398

KEYWORDS: Computed tomography, Image segmentation, Heart, Blood circulation, Data modeling, Data acquisition, 3D modeling, Cardiac imaging, Modeling and simulation, Neural networks

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Proceedings Article | 24 March 2016 Paper

Quantitative image quality evaluation for cardiac CT reconstructions

Hsin-Wu Tseng, Jiahua Fan, Matthew Kupinski, William Balhorn, Darin Okerlund

Proceedings Volume 9787, 978716 (2016) https://doi.org/10.1117/12.2208341

KEYWORDS: Computed tomography, Image quality, Reconstruction algorithms, Heart, Image processing, CT reconstruction, Temporal resolution, Electrocardiography, X-ray computed tomography, Error analysis, Motion estimation

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Proceedings Article | 19 March 2013 Paper

Task based assessment of a motion compensation algorithm via simulation of a moving stenotic vessel

Brian Nett, Jed Pack, Darin Okerlund

Proceedings Volume 8668, 86682B (2013) https://doi.org/10.1117/12.2006593

KEYWORDS: Image segmentation, Computed tomography, Computer simulations, Visualization, Image quality, Reconstruction algorithms, Motion estimation, Scanners, Arteries, Data acquisition

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Proceedings Article | 31 March 2011 Paper

Liver fat quantification using fast kVp-switching dual energy CT

Andras Kriston, Paulo Mendonça, Alvin Silva, Robert Paden, William Pavlicek, Dushyant Sahani, Benedek Janos Kis, Laszlo Rusko, Darin Okerlund, Rahul Bhotika

Proceedings Volume 7962, 79623W (2011) https://doi.org/10.1117/12.878206

KEYWORDS: Liver, Tissues, Signal attenuation, Dual energy imaging, Monte Carlo methods, Biopsy, X-ray computed tomography, Imaging spectroscopy, Visualization, Medicine

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Proceedings Article | 12 March 2011 Paper

Initial evaluation of virtual un-enhanced imaging derived from fast kVp-switching dual energy contrast enhanced CT for the abdomen

M. Joshi, P. Mendonca, D. Okerlund, P. Lamb, N. Kulkarni, D. Pinho, D. Sahani, R. Bhotika

Proceedings Volume 7962, 79621G (2011) https://doi.org/10.1117/12.878565

KEYWORDS: Dual energy imaging, Computed tomography, Image quality, Abdomen, Tissues, Kidney, Fast packet switching, Liver, Data acquisition, X-ray computed tomography

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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 | 13 March 2009 Paper

Cardiac imaging with multi-sector data acquisition in volumetric CT: variation of effective temporal resolution and its potential clinical consequences

Xiangyang Tang, Jiang Hsieh, Basel Taha, Melissa Vass, John Seamans, Darin Okerlund

Proceedings Volume 7258, 725832 (2009) https://doi.org/10.1117/12.812231

KEYWORDS: Temporal resolution, Data acquisition, Computed tomography, Cardiac imaging, Heart, Image restoration, Sensors, Diagnostics, Motion analysis, Medical imaging

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Proceedings Article | 25 March 2008 Paper

Cardiac imaging in diagnostic VCT using multi-sector data acquisition and image reconstruction: step-and-shoot scan vs. helical scan

Xiangyang Tang, Jiang Hsieh, John Seamans, Fang Dong, Darin Okerlund

Proceedings Volume 6913, 69131H (2008) https://doi.org/10.1117/12.769908

KEYWORDS: Data acquisition, Heart, Temporal resolution, Cardiac imaging, Image restoration, X-ray computed tomography, Sensors, Diagnostics, Computed tomography, Scanners

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Proceedings Article | 20 April 2005 Paper

Evaluation of an adaptive filtering algorithm for CT cardiac imaging with EKG modulated tube current

Jianying Li, Jiang Hsieh, Kelly Mohr, Darin Okerlund

Proceedings Volume 5745, (2005) https://doi.org/10.1117/12.595306

KEYWORDS: Digital filtering, Image filtering, Reconstruction algorithms, Computed tomography, Modulation, Algorithm development, Electrocardiography, Image resolution, Phase shift keying, Cardiac imaging

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Showing 5 of 11 publications

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