Prof. Colin Studholme Profile

Prof. Colin Studholme

Professor at Univ of Washington

SPIE Involvement:

Author

Publications (22)

Proceedings Article | 12 March 2018 Presentation + Paper

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

D. Hunt, M. Dighe, C. Gatenby, C. Studholme

Proceedings Volume 10578, 1057809 (2018) https://doi.org/10.1117/12.2294476

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

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Proceedings Article | 29 March 2016 Paper

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

Manjiri Dighe, Yun Jung Kim, Sharmishtaa Seshamani, Ania Blazejewska, Susan Mckown, Jason Caucutt, Christopher Gatenby, Colin Studholme

Proceedings Volume 9788, 97881H (2016) https://doi.org/10.1117/12.2217137

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

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Proceedings Article | 19 March 2015 Paper

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

Sharmishtaa Seshamani, Anna Blazejewska, Christopher Gatenby, Susan Mckown, Jason Caucutt, Manjiri Dighe, Colin Studholme

Proceedings Volume 9417, 94170N (2015) https://doi.org/10.1117/12.2082236

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

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Proceedings Article | 21 March 2014 Paper

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

Mengyuan Liu, Sharmishtaa Seshamani, Lisa Harrylock, Averi Kitsch, Steven Miller, Van Chau, Kenneth Poskitt, Francois Rousseau, Colin Studholme

Proceedings Volume 9034, 90341H (2014) https://doi.org/10.1117/12.2042426

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

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Proceedings Article | 12 March 2011 Paper

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

Kio Kim, Piotr Habas, Vidya Rajagopalan, Julia Scott, Francois Rousseau, A. James Barkovich, Orit Glenn, Colin Studholme

Proceedings Volume 7962, 79624D (2011) https://doi.org/10.1117/12.878489

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

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Proceedings Article | 11 March 2011 Paper

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

Piotr Habas, Vidya Rajagopalan, Julia Scott, Kio Kim, Ahmad Roosta, Francois Rousseau, A. James Barkovich, Orit Glenn, Colin Studholme

Proceedings Volume 7962, 79620O (2011) https://doi.org/10.1117/12.877749

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

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Proceedings Article | 13 March 2010 Paper

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

Kio Kim, Piotr Habas, Francois Rousseau, Orit Glenn, A. Barkovich, Meriam Koob, Jean-Louis Dietemann, Ashley J. Robinson, Kenneth J. Poskitt, Steven Miller, Colin Studholme

Proceedings Volume 7623, 76231I (2010) https://doi.org/10.1117/12.844542

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

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Proceedings Article | 27 March 2009 Paper

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

Piotr Habas, Kio Kim, Dharshan Chandramohan, Francois Rousseau, Orit Glenn, Colin Studholme

Proceedings Volume 7259, 725917 (2009) https://doi.org/10.1117/12.812425

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

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Proceedings Article | 26 March 2008 Paper

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

Karl Sjöstrand, Valerie Cardenas, Rasmus Larsen, Colin Studholme

Proceedings Volume 6914, 69140A (2008) https://doi.org/10.1117/12.770728

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

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Proceedings Article | 26 March 2008 Paper

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

Janet Blumenfeld, Colin Studholme, Julio Carballido-Gamio, Thomas Link, Sharmila Majumdar

Proceedings Volume 6914, 69140G (2008) https://doi.org/10.1117/12.770460

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

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Proceedings Article | 26 March 2007 Paper

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

Stathis Hadjidemetriou, Colin Studholme, Susanne Mueller, Mike Weiner, Norbert Schuff

Proceedings Volume 6512, 65121L (2007) https://doi.org/10.1117/12.711533

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

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Proceedings Article | 3 March 2007 Paper

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

Claudia Rodriguez-Carranza, P. Mukherjee, Daniel Vigneron, James Barkovich, Colin Studholme

Proceedings Volume 6512, 65120N (2007) https://doi.org/10.1117/12.710687

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

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Proceedings Article | 10 March 2006 Paper

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

Claudia Rodriguez-Carranza, Francois Rousseau, Bistra Iordanova, Orit Glenn, Daniel Vigneron, James Barkovich, Colin Studholme

Proceedings Volume 6144, 61441K (2006) https://doi.org/10.1117/12.652516

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

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Proceedings Article | 29 April 2005 Paper

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

Francois Rousseau, Andrew Maudsley, Andreas Ebel, Ammar Darkazanli, Patrice Weber, Krishnakumar Sivasankaran, Yingjian Yu, Colin Studholme

Proceedings Volume 5747, (2005) https://doi.org/10.1117/12.596345

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

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Proceedings Article | 12 May 2004 Paper

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

Corina Drapaca, Valerie Cardenas, Colin Studholme

Proceedings Volume 5370, (2004) https://doi.org/10.1117/12.535644

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

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Proceedings Article | 15 May 2003 Paper

MRI tissue segmentation incorporating a bias field modulated smoothness prior

Enmin Song, Valerie Cardenas, Diana Sacrey, Robert Blumenfeld, Michael Weiner, Colin Studholme

Proceedings Volume 5032, (2003) https://doi.org/10.1117/12.480852

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

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Proceedings Article | 3 July 2001 Paper

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

Colin Studholme, Valerie Cardenas, Michael Weiner

Proceedings Volume 4322, (2001) https://doi.org/10.1117/12.431130

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

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Proceedings Article | 6 June 2000 Paper

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

Colin Studholme, R. Todd Constable, James Duncan

Proceedings Volume 3979, (2000) https://doi.org/10.1117/12.387706

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

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Proceedings Article | 21 May 1999 Paper

Detecting small anatomical change with 3D serial MR subtraction images

Mark Holden, Erica Denton, J. Jarosz, T. Cox, Colin Studholme, David Hawkes, Derek Hill

Proceedings Volume 3661, (1999) https://doi.org/10.1117/12.348594

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

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Proceedings Article | 24 June 1998 Paper

Normalized entropy measure for multimodality image alignment

Colin Studholme, David Hawkes, Derek Hill

Proceedings Volume 3338, (1998) https://doi.org/10.1117/12.310835

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

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Proceedings Article | 16 April 1996 Paper

Comparison and evaluation of retrospective intermodality image registration techniques

Jay West, J. Michael Fitzpatrick, Matthew Wang, Benoit Dawant, Calvin Maurer, Robert Kessler, Robert Maciunas, Christian Barillot, Didier Lemoine, Andre Collignon, Frederik Maes, Paul Suetens, Dirk Vandermeulen, Petra van den Elsen, Paul Hemler, Sandy Napel, Thilaka Sumanaweera, Beth Harkness, Derek Hill, Colin Studholme, Gregoire Malandain, Xavier Pennec, Marilyn Noz, Gerald Maguire, Michael Pollack, Charles Pelizzari, Richard Robb, Dennis Hanson, Roger Woods

Proceedings Volume 2710, (1996) https://doi.org/10.1117/12.237936

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

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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 | 9 September 1994 Paper

Derek Hill, Colin Studholme, David Hawkes

Proceedings Volume 2359, (1994) https://doi.org/10.1117/12.185180

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

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