Dr. Gary E. Christensen Profile

Dr. Gary E. Christensen

Professor at Univ of Iowa

SPIE Involvement:

Author

Publications (23)

Proceedings Article | 2 March 2018 Presentation + Paper

Sensitivity analysis of Jacobian determinant used in treatment planning for lung cancer

Wei Shao, Sarah Gerard, Yue Pan, Taylor Patton, Joseph Reinhardt, Oguz Durumeric, John Bayouth, Gary Christensen

Proceedings Volume 10574, 1057418 (2018) https://doi.org/10.1117/12.2293920

KEYWORDS: Lung, Computed tomography, Error analysis, Image registration, Lung cancer, Biological research, Radiotherapy, Visualization, Tissues, Clinical trials

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Proceedings Article | 16 April 2012 Paper

Estimation of lung lobar sliding using image registration

Ryan Amelon, Kunlin Cao, Joseph Reinhardt, Gary Christensen, Madhavan Raghavan

Proceedings Volume 8317, 83171H (2012) https://doi.org/10.1117/12.911614

KEYWORDS: Lung, Image registration, Computed tomography, Image segmentation, Tissues, Motion analysis, Error analysis, Performance modeling, Distortion, Finite element methods

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Proceedings Article | 6 April 2012 Paper

Correlation of measures of regional lung ventilation from 4DCT vs. hyperpolarized helium-3 MR

Kai Ding, Kunlin Cao, Wilson Miller, Gary Christensen, Joseph Reinhardt, Stanley Benedict, Bruce Libby, Ke Sheng

Proceedings Volume 8317, 83171E (2012) https://doi.org/10.1117/12.912793

KEYWORDS: Lung, Image registration, Tissues, Magnetic resonance imaging, Computed tomography, Radiotherapy, Transform theory, 3D image processing, 3D acquisition, Image processing

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Proceedings Article | 13 March 2010 Paper

Evaluation of five non-rigid image registration algorithms using the NIREP framework

Ying Wei, Gary Christensen, Joo Hyun Song, David Rudrauf, Joel Bruss, Jon Kuhl, Thomas Grabowski

Proceedings Volume 7623, 76232L (2010) https://doi.org/10.1117/12.844616

KEYWORDS: Image registration, Image segmentation, Databases, Error analysis, Detection and tracking algorithms, Statistical analysis, Image analysis, Image processing algorithms and systems, Samarium, Visualization

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Proceedings Article | 13 March 2010 Paper

Tissue volume and vesselness measure preserving nonrigid registration of lung CT images

Kunlin Cao, Kai Ding, Gary Christensen, Joseph Reinhardt

Proceedings Volume 7623, 762309 (2010) https://doi.org/10.1117/12.844541

KEYWORDS: Lung, Image registration, Tissues, Computed tomography, Error analysis, Blood vessels, Image processing, Algorithm development, Data acquisition, Image segmentation

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Proceedings Article | 9 March 2010 Paper

Human airway tree structure query atlas

Gary Christensen, Nathan Burnette, Weichen Gao, Matineh Shaker, Joseph Reinhardt, Janice Cook-Granroth, Geoffrey McLennan, Eric Hoffman

Proceedings Volume 7626, 762611 (2010) https://doi.org/10.1117/12.844596

KEYWORDS: Lung, Databases, Computed tomography, Image segmentation, Human-machine interfaces, Data acquisition, Diagnostics, Computer engineering, Oncology, Medicine

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Proceedings Article | 27 February 2009 Paper

Registration-based regional lung mechanical analysis: retrospectively reconstructed dynamic imaging versus static breath-hold image acquisition

Kai Ding, Kunlin Cao, Gary Christensen, Eric Hoffman, Joseph Reinhardt

Proceedings Volume 7262, 72620D (2009) https://doi.org/10.1117/12.813694

KEYWORDS: Lung, Image registration, Computed tomography, Tissues, Xenon, Image acquisition, 3D image processing, Error analysis, Image analysis, 3D acquisition

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Proceedings Article | 8 March 2007 Paper

Three-dimensional histopathology of lung cancer with multimodality image registration

Jessica de Ryk, Jamie Weydert, Gary Christensen, Jacqueline Thiesse, Eman Namati, Joseph Reinhardt, Eric Hoffman, Geoffrey McLennan

Proceedings Volume 6512, 65122F (2007) https://doi.org/10.1117/12.710597

KEYWORDS: Tissues, Tumors, Lung cancer, Image registration, Neural networks, 3D image processing, Computed tomography, Cancer, Lung, Microscopy

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Proceedings Article | 3 March 2007 Paper

Active index model: a unique approach for regional quantitative morphometry in longitudinal and cross-sectional studies

P. Saha, H. Zhang, M. Sonka, G. Christensen, C. Rajapakse

Proceedings Volume 6512, 65121B (2007) https://doi.org/10.1117/12.709022

KEYWORDS: Bone, Image segmentation, Magnetic resonance imaging, Image registration, Statistical analysis, 3D modeling, Diagnostics, Lithium, Associative arrays, Shape analysis

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Proceedings Article | 10 March 2006 Paper

Modeling lung motion using consistent image registration in four-dimensional computed tomography for radiation therapy

Wei Lu, Joo Hyun Song, Gary Christensen, Parag Parikh, Jeffrey Bradley, Daniel Low

Proceedings Volume 6144, 61442L (2006) https://doi.org/10.1117/12.652761

KEYWORDS: Lung, Image registration, 4D CT imaging, Motion models, Radiotherapy, Computed tomography, 3D image processing, Image segmentation, Tissues, Error analysis

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Proceedings Article | 14 April 2005 Paper

Estimation of regional lung expansion via 3D image registration

Yan Pan, Dinesh Kumar, Eric Hoffman, Gary Christensen, Geoffrey McLennan, Joo Hyun Song, Alan Ross, Brett Simon, Joseph Reinhardt

Proceedings Volume 5746, (2005) https://doi.org/10.1117/12.596617

KEYWORDS: Lung, Image registration, Image segmentation, Tissues, 3D image processing, Computed tomography, X-ray computed tomography, Scanners, Magnetic resonance imaging, Biological research

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Proceedings Article | 30 April 2004 Paper

Automated 4D lung computed tomography reconstruction during free breathing for conformal radiation therapy

Issam El Naqa, Daniel Low, Gary Christensen, Parag Parikh, Joo Hyun Song, Michelle Nystrom, Wei Lu, Joseph Deasy, James Hubenschmidt, Sasha Wahab, Sasa Mutic, Anurag Singh, Jeffrey Bradley

Proceedings Volume 5369, (2004) https://doi.org/10.1117/12.536141

KEYWORDS: Computed tomography, Lung, Spirometry, Motion measurement, Radiotherapy, Scanners, Optical flow, Tumors, Optical tracking, Image registration

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SPIE Journal Paper | 1 January 2003

Invertibility and transitivity analysis for nonrigid image registration

Gary Christensen, Hans Johnson

JEI, Vol. 12, Issue 01, (January 2003) https://doi.org/10.1117/12.10.1117/1.1526494

KEYWORDS: Image registration, Magnetic resonance imaging, Computed tomography, Detection and tracking algorithms, 3D image processing, Error analysis, Head, Brain, Image analysis, Neuroimaging

Proceedings Article | 9 May 2002 Paper

Analysis of a new method for consistent large-deformation elastic image registration

Jaincun He, Gary Christensen, Jay Rubenstein, Ge Wang

Proceedings Volume 4684, (2002) https://doi.org/10.1117/12.467047

KEYWORDS: Ear, Image registration, Computed tomography, Image analysis, Tolerancing, Germanium, Process modeling, Medical imaging, Image processing, Image restoration

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Proceedings Article | 24 April 2002 Paper

3D intersubject warping and registration of pulmonary CT images for a human lung model

Baojun Li, Gary Christensen, John Dill, Eric Hoffman, Joseph Reinhardt

Proceedings Volume 4683, (2002) https://doi.org/10.1117/12.463598

KEYWORDS: Lung, Image registration, Computed tomography, 3D image processing, Image segmentation, 3D modeling, Image processing, Visualization, Computer simulations, Scanners

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Proceedings Article | 3 July 2001 Paper

Evaluating template bias when synthesizing population averages

Blake Carlson, Gary Christensen, Hans Johnson, Michael Vannier

Proceedings Volume 4322, (2001) https://doi.org/10.1117/12.431126

KEYWORDS: Skull, Brain, Magnetic resonance imaging, Neuroimaging, Image registration, Computed tomography, 3D image processing, Medical imaging, Distance measurement, Image analysis

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Proceedings Article | 6 June 2000 Paper

Validation of probabilistic anatomical shape atlases

Hans Johnson, Gary Christensen, Jeffrey Marsh, Michael Vannier

Proceedings Volume 3979, (2000) https://doi.org/10.1117/12.387730

KEYWORDS: Image registration, Associative arrays, Brain mapping, Data modeling, Magnetic resonance imaging, Brain, Computed tomography, Head, Detection and tracking algorithms, Image segmentation

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Proceedings Article | 21 May 1999 Paper

Synthesizing average 3D anatomical shapes using deformable templates

Gary Christensen, Hans Johnson, John Haller, Jenny Melloy, Michael Vannier, Jeffrey Marsh

Proceedings Volume 3661, (1999) https://doi.org/10.1117/12.348613

KEYWORDS: Brain, Magnetic resonance imaging, Skull, Medical imaging, Computed tomography, 3D image processing, Neuroimaging, 3D acquisition, 3D modeling, Nose

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Proceedings Article | 21 May 1999 Paper

Midsagittal surface measurement of the head: an assessment of craniofacial asymmetry

Gary Christensen, Hans Johnson, Tron Darvann, Nuno Hermann, Jeffrey Marsh

Proceedings Volume 3661, (1999) https://doi.org/10.1117/12.348617

KEYWORDS: Visualization, Skull, Head, Surgery, Distance measurement, 3D metrology, 3D modeling, Data modeling, 3D visualizations, Brain

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Proceedings Article | 20 October 1997 Paper

Deformable anatomical templates for brachytherapy treatment planning in radiotherapy of cervical cancer

Gary Christensen, Jeffrey Williamson, K. Chao, Michael Miller, F. So, Michael Vannier

Proceedings Volume 3168, (1997) https://doi.org/10.1117/12.292779

KEYWORDS: X-ray computed tomography, Cervical cancer, Image registration, Radiotherapy, 3D image processing, Vagina, Cervix, Bladder, Rectum, 3D scanning

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Proceedings Article | 11 August 1995 Paper

Hierarchical brain mapping via a generalized Dirichlet solution for mapping brain manifolds

Sarang Joshi, Michael Miller, Gary Christensen, Ayan Banerjee, Tom Coogan, Ulf Grenander

Proceedings Volume 2573, (1995) https://doi.org/10.1117/12.216420

KEYWORDS: Brain, Brain mapping, Distance measurement, Molybdenum, Electrical engineering, Medicine, Neuroscience, Image registration, Physics, Kinematics

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Proceedings Article | 11 August 1995 Paper

Mapping of hyperelastic deformable templates using the finite element method

Richard Rabbitt, Jeffrey Weiss, Gary Christensen, Michael Miller

Proceedings Volume 2573, (1995) https://doi.org/10.1117/12.216419

KEYWORDS: Chemical elements, Mechanics, Data modeling, Sensors, Optical sensors, Image sensors, Finite element methods, Medical imaging, Image registration, Associative arrays

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Proceedings Article | 12 May 1995 Paper

Comparison of automated and manual segmentation of hippocampus MR images

John Haller, Gary Christensen, Michael Miller, Sarang Joshi, Mokhtar Gado, John Csernansky, Michael Vannier

Proceedings Volume 2434, (1995) https://doi.org/10.1117/12.208692

KEYWORDS: Image segmentation, Magnetic resonance imaging, Brain, Neuroimaging, 3D image processing, Head, Magnetism, Brain mapping, Scanning electron microscopy, Medicine

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The precision and accuracy of area estimates from magnetic resonance (MR) brain images and using manual and automated segmentation methods are determined. Areas of the human hippocampus were measured to compare a new automatic method of segmentation with regions of interest drawn by an expert. MR images of nine normal subjects and nine schizophrenic patients were acquired with a 1.5-T unit (Siemens Medical Systems, Inc., Iselin, New Jersey). From each individual MPRAGE 3D volume image a single comparable 2-D slice (matrix equals 256 X 256) was chosen which corresponds to the same coronal slice of the hippocampus. The hippocampus was first manually segmented, then segmented using high dimensional transformations of a digital brain atlas to individual brain MR images. The repeatability of a trained rater was assessed by comparing two measurements from each individual subject. Variability was also compared within and between subject groups of schizophrenics and normal subjects. Finally, the precision and accuracy of automated segmentation of hippocampal areas were determined by comparing automated measurements to manual segmentation measurements made by the trained rater on MR and brain slice images. The results demonstrate the high repeatability of area measurement from MR images of the human hippocampus. Automated segmentation using high dimensional transformations from a digital brain atlas provides repeatability superior to that of manual segmentation. Furthermore, the validity of automated measurements was demonstrated by a high correlation with manual segmentation measurements made by a trained rater. Quantitative morphometry of brain substructures (e.g. hippocampus) is feasible by use of a high dimensional transformation of a digital brain atlas to an individual MR image. This method automates the search for neuromorphological correlates of schizophrenia by a new mathematically robust method with unprecedented sensitivity to small local and regional differences.

Showing 5 of 23 publications

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