Prof. Colin Studholme Profile

Prof. Colin Studholme

Professor at Univ of Washington

SPIE Involvement:

Conference Program Committee | Author

Publications (22)

PROCEEDINGS ARTICLE | March 12, 2018

Comparing diffusion tensor and spherical harmonic tractography for in utero studies of fetal brain connectivity

Proc. SPIE. 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging

KEYWORDS: Diffusion weighted imaging, Data modeling, Diffusion, Deconvolution, Neuroimaging, Motion models, Diffusion tensor imaging, Brain, Fetus

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PROCEEDINGS ARTICLE | March 29, 2016

Regional placental blood oxygen level dependent (BOLD) changes with gestational age in normally developing pregnancies using long duration R2* mapping in utero

Proc. SPIE. 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging

KEYWORDS: Statistical analysis, Tissues, Blood, Magnetic resonance imaging, Image segmentation, Image processing, Image registration, Oxygen, Blood oxygen saturation, In vitro testing, Functional magnetic resonance imaging, Brain, Fetus

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PROCEEDINGS ARTICLE | March 19, 2015

Comparing consistency of R2* and T2*-weighted BOLD analysis of resting state fetal fMRI

Proc. SPIE. 9417, Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging

KEYWORDS: Independent component analysis, Magnetic resonance imaging, Distortion, Head, Associative arrays, Motion estimation, Brain mapping, Functional magnetic resonance imaging, Brain, Fetus

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PROCEEDINGS ARTICLE | March 21, 2014

Spatially adapted augmentation of age-specific atlas-based segmentation using patch-based priors

Proc. SPIE. 9034, Medical Imaging 2014: Image Processing

KEYWORDS: Tissues, Magnetic resonance imaging, Image segmentation, Associative arrays, Traumatic brain injury, Neuroimaging, Algorithm development, Expectation maximization algorithms, Brain mapping, Brain

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PROCEEDINGS ARTICLE | March 12, 2011

SLIMMER: SLIce MRI motion estimation and reconstruction tool for studies of fetal anatomy

Proc. SPIE. 7962, Medical Imaging 2011: Image Processing

KEYWORDS: 3D acquisition, 3D image reconstruction, Magnetic resonance imaging, 3D modeling, Medical imaging, Head, Reconstruction algorithms, Motion estimation, 3D image processing, Fetus

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PROCEEDINGS ARTICLE | March 11, 2011

Detection and mapping of delays in early cortical folding derived from in utero MRI

Proc. SPIE. 7962, Medical Imaging 2011: Image Processing

KEYWORDS: Tissues, Magnetic resonance imaging, Image segmentation, Image processing, Control systems, Neuroimaging, Natural surfaces, Brain mapping, Brain, Fetus

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PROCEEDINGS ARTICLE | March 13, 2010

Reconstruction of a geometrically correct diffusion tensor image of a moving human fetal brain

Proc. SPIE. 7623, Medical Imaging 2010: Image Processing

KEYWORDS: Diffusion weighted imaging, Tissues, Magnetic resonance imaging, Diffusion, Image registration, Neuroimaging, 3D image processing, Diffusion tensor imaging, Brain, Fetus

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PROCEEDINGS ARTICLE | March 27, 2009

Statistical model of laminar structure for atlas-based segmentation of the fetal brain from in utero MR images

Proc. SPIE. 7259, Medical Imaging 2009: Image Processing

KEYWORDS: Statistical analysis, 3D image reconstruction, Tissues, Magnetic resonance imaging, Image segmentation, Neuroimaging, Natural surfaces, Expectation maximization algorithms, Brain, Fetus

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PROCEEDINGS ARTICLE | March 26, 2008

Three-dimensional image registration of MR proximal femur images for the analysis of trabecular bone parameters

Proc. SPIE. 6914, Medical Imaging 2008: Image Processing

KEYWORDS: Magnetic resonance imaging, Image segmentation, Image processing, Image resolution, Image analysis, Image registration, Bone, Medical imaging, In vivo imaging, 3D image processing

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PROCEEDINGS ARTICLE | March 26, 2008

A generalization of voxel-wise procedures for high-dimensional statistical inference using ridge regression

Proc. SPIE. 6914, Medical Imaging 2008: Image Processing

KEYWORDS: Principal component analysis, Statistical analysis, Cognitive modeling, Data modeling, Magnetic resonance imaging, Error analysis, Statistical methods, Statistical modeling, Statistical inference, Brain

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PROCEEDINGS ARTICLE | March 26, 2007

Restoration of MRI data for field nonuniformities using high order neighborhood statistics

Proc. SPIE. 6512, Medical Imaging 2007: Image Processing

KEYWORDS: Optical spheres, Tissues, Magnetic resonance imaging, Image segmentation, Image restoration, Image registration, Head, Deconvolution, Image information entropy, Brain

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PROCEEDINGS ARTICLE | March 3, 2007

Comparing 3D Gyrification Index and area-independent curvature-based measures in quantifying neonatal brain folding

Proc. SPIE. 6512, Medical Imaging 2007: Image Processing

KEYWORDS: 3D acquisition, Magnetic resonance imaging, Interfaces, 3D metrology, Convolution, In vivo imaging, Neuroimaging, Binary data, 3D image processing, Brain

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PROCEEDINGS ARTICLE | March 10, 2006

An ISO-surface folding analysis method applied to premature neonatal brain development

Proc. SPIE. 6144, Medical Imaging 2006: Image Processing

KEYWORDS: Magnetic resonance imaging, Image segmentation, Image processing, Interfaces, Data acquisition, Time metrology, Convolution, In vivo imaging, Natural surfaces, Brain

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PROCEEDINGS ARTICLE | April 29, 2005

Evaluation of sub-voxel registration accuracy between MRI and 3D MR spectroscopy of the brain

Proc. SPIE. 5747, Medical Imaging 2005: Image Processing

KEYWORDS: 3D acquisition, Magnetic resonance imaging, Spectroscopy, Error analysis, Imaging spectroscopy, Image registration, Data acquisition, Neuroimaging, Brain mapping, Brain

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PROCEEDINGS ARTICLE | May 12, 2004

Robust space-time extraction of ventricular surface evolution using multiphase level sets

Proc. SPIE. 5370, Medical Imaging 2004: Image Processing

KEYWORDS: Tissues, Magnetic resonance imaging, Image segmentation, Interfaces, Image resolution, Neuroimaging, Natural surfaces, 3D image processing, Dementia, Brain

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PROCEEDINGS ARTICLE | May 15, 2003

MRI tissue segmentation incorporating a bias field modulated smoothness prior

Proc. SPIE. 5032, Medical Imaging 2003: Image Processing

KEYWORDS: Gold, Statistical analysis, Tissues, Magnetic resonance imaging, Image segmentation, Image processing, Medical imaging, Signal processing, Brain mapping, Brain

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PROCEEDINGS ARTICLE | July 3, 2001

Multiscale image and multiscale deformation of brain anatomy for building average brain atlases

Proc. SPIE. 4322, Medical Imaging 2001: Image Processing

KEYWORDS: Roentgenium, Tissues, Magnetic resonance imaging, Image resolution, Image registration, Neuroimaging, Algorithm development, Alzheimer's disease, Brain mapping, Brain

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PROCEEDINGS ARTICLE | June 6, 2000

Phantom-based investigation of nonrigid registration constraints in mapping fMRI to anatomical MRI

Proc. SPIE. 3979, Medical Imaging 2000: Image Processing

KEYWORDS: Magnetic resonance imaging, Ions, Magnetism, Distortion, Image registration, Data acquisition, Signal processing, Associative arrays, Functional magnetic resonance imaging, Tin

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PROCEEDINGS ARTICLE | May 21, 1999

Detecting small anatomical change with 3D serial MR subtraction images

Proc. SPIE. 3661, Medical Imaging 1999: Image Processing

KEYWORDS: Visualization, Calibration, Magnetic resonance imaging, Scanners, Ions, Control systems, Image registration, Neuroimaging, 3D image processing, Brain

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PROCEEDINGS ARTICLE | June 24, 1998

Normalized entropy measure for multimodality image alignment

Proc. SPIE. 3338, Medical Imaging 1998: Image Processing

KEYWORDS: Image restoration, Image resolution, Image registration, Medical imaging, Computed tomography, Neuroimaging, Positron emission tomography, 3D image processing, Image information entropy, Brain

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PROCEEDINGS ARTICLE | April 16, 1996

Comparison and evaluation of retrospective intermodality image registration techniques

Proc. SPIE. 2710, Medical Imaging 1996: Image Processing

KEYWORDS: Gold, Magnetic resonance imaging, Image segmentation, Image processing, Error analysis, Distortion, Image registration, Computed tomography, Positron emission tomography, Brain

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All retrospective image registration methods have attached to them some intrinsic estimate of registration error. However, this estimate of accuracy may not always be a good indicator of the distance between actual and estimated positions of targets within the cranial cavity. This paper describes a project whose principal goal is to use a prospective method based on fiducial markers as a 'gold standard' to perform an objective, blinded evaluation of the accuracy of several retrospective image-to-image registration techniques. Image volumes of three modalities -- CT, MR, and PET -- were taken of patients undergoing neurosurgery at Vanderbilt University Medical Center. These volumes had all traces of the fiducial markers removed, and were provided to project collaborators outside Vanderbilt, who then performed retrospective registrations on the volumes, calculating transformations from CT to MR and/or from PET to MR, and communicated their transformations to Vanderbilt where the accuracy of each registration was evaluated. In this evaluation the accuracy is measured at multiple 'regions of interest,' i.e. areas in the brain which would commonly be areas of neurological interest. A region is defined in the MR image and its centroid C is determined. Then the prospective registration is used to obtain the corresponding point C' in CT or PET. To this point the retrospective registration is then applied, producing C' in MR. Statistics are gathered on the target registration error (TRE), which is the disparity between the original point C and its corresponding point C'. A second goal of the project is to evaluate the importance of correcting geometrical distortion in MR images, by comparing the retrospective TRE in the rectified images, i.e., those which have had the distortion correction applied, with that of the same images before rectification. This paper presents preliminary results of this study along with a brief description of each registration technique and an estimate of both preparation and execution time needed to perform the registration .

PROCEEDINGS ARTICLE | September 9, 1994

Voxel similarity measures for automated image registration

Proc. SPIE. 2359, Visualization in Biomedical Computing 1994

KEYWORDS: Magnetic resonance imaging, Image restoration, Image resolution, Image registration, Head, Image enhancement, Computed tomography, Algorithm development, Gadolinium, Positron emission tomography

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