Dr. Stephen Aylward Profile

Dr. Stephen Aylward

Senior Director of Operations - North Carolina at Kitware Inc

SPIE Involvement:

Author | Editor | Instructor

Area of Expertise:

ITK , Statistical Pattern Recognition , Medical Image Analysis , Vascular Image Analysis , Software Engineering , Open Science

Websites:

Company Website | Personal Website

Stephen R. Aylward, Ph.D. is Senior Director of Operations - North Carolina and a Managing Partner at Kitware, Inc. Dr. Aylward is also an Adjunct Associate Professor in the Department of Computer Science at UNC, Chapel Hill. Stephen founded Kitware’s office in North Carolina in 2006. Its members conduct applied image analysis research and application development in the medical, computer vision, and scientific visualization fields. Dr. Aylward’s research has recently focused on developing model-to-image registration strategies for image guided surgery, vascular network characterization for disease diagnosis, and digital library technologies, e.g., the Insight Journal, http://www.insight-journal.org.

Dr. Aylward is also an Associate Editor of IEEE Transactions on Medical Imaging and the elected president of the Insight Software Consortium – a non-profit agency that promotes free software for medical image analysis. Stephen received a B.S. in computer science in 1988 from Purdue University, an M.S. in artificial intelligence in 1989 from the Georgia Institute of Technology, and a Ph.D. in medical image processing in 1997 from UNC. Prior to joining Kitware, Stephen was a tenured Associate Professor of Radiology at UNC.

Proceedings Article | 19 May 2016 Paper

Acoustic angiography: a new high frequency contrast ultrasound technique for biomedical imaging

Sarah Shelton, Brooks Lindsey, Ryan Gessner, Yueh Lee, Stephen Aylward, Hyunggyun Lee, Emmanuel Cherin, F. Stuart Foster, Paul Dayton

Proceedings Volume 9871, 987109 (2016) https://doi.org/10.1117/12.2229179

KEYWORDS: Acoustics, Angiography, Ultrasonography, Transducers, Tissues, Image resolution, Tumors, Imaging systems, In vivo imaging, Cancer

Read Abstract +

Proceedings Article | 21 March 2014 Paper

Variability sensitivity of dynamic texture based recognition in clinical CT data

Roland Kwitt, Sharif Razzaque, Jeffrey Lowell, Stephen Aylward

Proceedings Volume 9034, 903420 (2014) https://doi.org/10.1117/12.2043271

KEYWORDS: Databases, Kidney, Data modeling, Video, Ultrasonography, Computed tomography, Data acquisition, Transducers, Performance modeling, Medical imaging

Read Abstract +

Proceedings Article | 17 October 2013 Open Access

Trends and challenges in open source software (Presentation Video)

Stephen Aylward

Proceedings Volume 8855, 885501 (2013) https://doi.org/10.1117/12.2030336

Read Abstract +

DOWNLOAD PAPER

Proceedings Article | 29 March 2013 Paper

3D of brain shape and volume after cranial vault remodeling surgery for craniosynostosis correction in infants

Beatriz Paniagua, Omri Emodi, Jonathan Hill, James Fishbaugh, Luiz Pimenta, Stephen Aylward, Enquobahrie Andinet, Guido Gerig, John Gilmore, John van Aalst, Martin Styner

Proceedings Volume 8672, 86720V (2013) https://doi.org/10.1117/12.2006524

KEYWORDS: Brain, Control systems, Skull, Image segmentation, Surgery, Magnetic resonance imaging, Neuroimaging, Shape analysis, Computed tomography, 3D modeling

Read Abstract +

Proceedings Article | 15 March 2013 Paper

Accelerating ultrasound image analysis research through publically available database

Vikas Revanna Shivaprabhu, Andinet Enquobahrie, Zach Mullen, Stephen Aylward

Proceedings Volume 8675, 867517 (2013) https://doi.org/10.1117/12.2007577

KEYWORDS: Databases, Ultrasonography, Image acquisition, Image registration, Image analysis, Data acquisition, Scanners, Image processing, Magnetic resonance imaging, Liver

Read Abstract +

Proceedings Article | 14 March 2013 Paper

Patient-specific port placement for laparoscopic surgery using atlas-based registration

Andinet Enquobahrie, Vikas Shivaprabhu, Stephen Aylward, Julien Finet, Kevin Cleary, Ron Alterovitz

Proceedings Volume 8671, 86711M (2013) https://doi.org/10.1117/12.2006461

KEYWORDS: Surgery, Visualization, Laparoscopy, 3D modeling, 3D acquisition, Cameras, Image registration, Medical imaging, Data modeling, Detection and tracking algorithms

Read Abstract +

Proceedings Article | 2 March 2011 Paper

Approach-specific multi-grid anatomical modeling for neurosurgery simulation with public-domain and open-source software

Michel Audette, Denis Rivière, Charles Law, Luis Ibanez, Stephen Aylward, Julien Finet, Xunlei Wu, Matthew Ewend

Proceedings Volume 7964, 79642J (2011) https://doi.org/10.1117/12.877883

KEYWORDS: Brain, Tissues, Skull, Pathology, Data modeling, Natural surfaces, Surgery, Visualization, Binary data, Blood vessels

Read Abstract +

Proceedings Article | 27 March 2009 Paper

Evaluation of atlas based mouse brain segmentation

Joohwi Lee, Julien Jomier, Stephen Aylward, Mike Tyszka, Sheryl Moy, Jean Lauder, Martin Styner

Proceedings Volume 7259, 725943 (2009) https://doi.org/10.1117/12.812762

KEYWORDS: Image segmentation, Brain, Image registration, Tissues, Neuroimaging, Skull, Calibration, Magnetic resonance imaging, Brain mapping, Diffusion

Read Abstract +

Proceedings Article | 13 March 2009 Paper

A digital archiving system and distributed server-side processing of large datasets

Julien Jomier, Stephen Aylward, Charles Marion, Joowhi Lee, Martin Styner

Proceedings Volume 7264, 726413 (2009) https://doi.org/10.1117/12.812227

KEYWORDS: Visualization, Image processing, Distributed computing, Analytical research, Computing systems, Medical imaging, Databases, Data storage, Human-machine interfaces, Brain

Read Abstract +

Proceedings Article | 1 April 2008 Paper

A tool for computer-aided diagnosis of retinopathy of prematurity

Zheen Zhao, David Wallace, Sharon Freedman, Stephen Aylward

Proceedings Volume 6915, 69152W (2008) https://doi.org/10.1117/12.769030

KEYWORDS: Blood vessels, Photography, Computer aided diagnosis and therapy, Diagnostics, Eye, Image analysis, Standards development, Computer simulations, Reconstruction algorithms, Retina

Read Abstract +

Proceedings Article | 21 March 2007 Paper

The Image-Guided Surgery ToolKit IGSTK: an open source C++ software toolkit

Peng Cheng, Luis Ibanez, David Gobbi, Kevin Gary, Stephen Aylward, Julien Jomier, Andinet Enquobahrie, Hui Zhang, Hee-su Kim, M. Brian Blake, Kevin Cleary

Proceedings Volume 6516, 65160A (2007) https://doi.org/10.1117/12.719562

KEYWORDS: Software development, Image-guided intervention, Safety, Logic, C++, Visualization, Optical tracking, Computer programming, Control systems, Open source software

Read Abstract +

Proceedings Article | 10 March 2006 Paper

IGSTK: framework and example application using an open source toolkit for image-guided surgery applications

Peng Cheng, Hui Zhang, Hee-su Kim, Kevin Gary, M. Brian Blake, David Gobbi, Stephen Aylward, Julien Jomier, Andinet Enquobahrie, Rick Avila, Luis Ibanez, Kevin Cleary

Proceedings Volume 6141, 61411Y (2006) https://doi.org/10.1117/12.660583

KEYWORDS: Biopsy, Image-guided intervention, Prototyping, Image registration, Open source software, Visualization, Computed tomography, Software development, Surgery, Safety

Read Abstract +

Proceedings Article | 6 April 2005 Open Access

Visualizing blood vessel trees in three dimensions: clinical applications

Elizabeth Bullitt, Stephen Aylward

Proceedings Volume 5749, (2005) https://doi.org/10.1117/12.604746

KEYWORDS: Tumors, Visualization, Image segmentation, 3D displays, 3D image processing, X-rays, Image registration, Surgery, Angiography, Blood vessels

Read Abstract +

DOWNLOAD PAPER

Proceedings Article | 26 May 1999 Paper

Evaluation of digital processing methods for the display of digital mammography

Bradley Hemminger, Elodia Cole, Shuquan Zong, Martin Yaffe, Stephen Aylward, Andrew Maidment, Mark Williams, Loren Niklason, Richard Johnston, Etta Pisano

Proceedings Volume 3658, (1999) https://doi.org/10.1117/12.349450

KEYWORDS: Image processing, Mammography, Digital mammography, Breast, Digital image processing, Printing, Image enhancement, Algorithm development, Digital imaging, Standards development

Read Abstract +

Proceedings Article | 9 September 1994 Paper

Spatially invariant classification of tissues in MR images

Stephen Aylward, James Coggins, Ted Cizadlo, Nancy Andreasen

Proceedings Volume 2359, (1994) https://doi.org/10.1117/12.185196

KEYWORDS: Data modeling, Tissues, Magnetic resonance imaging, Image processing, Matrices, Image classification, Statistical modeling, Cerebellum, Magnetism, Statistical methods

Read Abstract +

Inhomogeneities in the fields of magnetic resonance (MR) systems cause the statistical characteristics of tissue classes to vary within the resulting MR images. These inhomogeneities must be taken into consideration when designing an algorithm for automated tissue classification. The traditional approach in image processing would be to apply a gain field correction technique to remove the inhomogeneities from the images. Statistical solutions would most likely focus on including spatial information in the feature space of the classifier so that it can be trained to model and adjust for the inhomogeneities. This paper will prove that neither of these general approaches offer a complete and viable solution. This paper will prove that neither of these general approaches offers a complete and viable solution. This paper will in fact show that not only do the inhomogeneities modify the local mean and variance of a tissue class as is commonly accepted, but the inhomogeneities also induce a rotation of the covariance matrices. As a result, gain field correction techniques cannot compensate for all of the artifacts associated with inhomogeneities. Additionally, it will be demonstrated that while statistical methods can capture all of the anomalies, the across patient and across time variations of the inhomogeneities necessitate frequent and time consuming retraining of any Bayesian classifier. This paper introduces a two stage process for MR tissue classification which addresses both of these issues by utilizing techniques from both image processing and statistics. First, a band-pass mean field corrector is used to alleviate the mean and variance deformations in each image. Then, using a kernel mixture model classifier couple to an interactive data augmentation tool, the user can selectively refine and explore the class representations for localized regions of the image and thereby capture the rotation of the covariance matrices. This approach is shown to outperform Gaussian classifiers and 4D mixture modeling techniques when both the final accuracy and user time requirements are considered.

Proceedings Article | 19 August 1993 Paper

Design techniques for the control of errors in backpropagation neural networks

Daniel St. Clair, Gerald Peterson, Stephen Aylward, William Bond

Proceedings Volume 1966, (1993) https://doi.org/10.1117/12.152636

KEYWORDS: Neural networks, Error analysis, Data modeling, Network architectures, Artificial neural networks, Aluminum, Molybdenum, Statistical analysis, Adaptive optics, Error control coding

Read Abstract +

Showing 5 of 16 publications

SPIE Conference Volume | 5 May 2014

Medical Imaging 2014: Computer-Aided Diagnosis

SPIE Conference Volume | 18 April 2013

Medical Imaging 2013: Computer-Aided Diagnosis

Conference Committee Involvement (15)

Computer-Aided Diagnosis

12 February 2018 | Houston, Texas, United States

Computer-Aided Diagnosis

13 February 2017 | Orlando, Florida, United States

Computer-Aided Diagnosis Posters

13 February 2017 | Orlando, FL, United States

Computer-Aided Diagnosis

28 February 2016 | San Diego, California, United States

Computer-Aided Diagnosis

22 February 2015 | Orlando, Florida, United States

Showing 5 of 15 Conference Committees

Course Instructor

SC1182: ITK in Biomedical Research and Commercial Applications

The Insight Segmentation and Registration Toolkit (www.itk.org) has become a standard in academia and industry for medical image analysis. In recent years, the ITK developers' community has focused on providing programming interfaces to ITK from Python, Java, and Javascript and making ITK available via leading applications such as Slicer and ImageJ. In this course we present best practices for taking advantage of ITK in your imaging research and commercial products. Via interactive examples that attendees can run on their laptops during the course, we show how ITK can speed research and commercial product development. We demonstrate how script writing and interactive GUIs can be used to access the algorithms in ITK and the multitude of ITK extensions that are freely available on the web. We also cover the opportunities and challenges with using open-source software in research and in commercial applications: from prototypes that can lead to venture capital funding to applications for first-in-human trials and ultimately for regulatory approval.

Expand Description +

SC538: Medical Image Analysis with ITK and Related Open-Source Software

This course introduces attendees to select open-source efforts in the field of medical image analysis. Opportunities for users and developers are presented. The course particularly focuses on the open-source Insight Toolkit (ITK) for medical image segmentation and registration. The course describes the procedure for downloading and installing the toolkit and covers the use of its data representation and filtering classes. Attendees are shown how ITK can be used in their research, rapid prototyping, and application development. COURSE SCHEDULE: Stephen Aylward, Kitware, Inc. – Chapel Hill Office • The Insight Software Consortium: contributing and using open-source • The architecture and installation of the Insight Toolkit Josh Cates, Univ. of Utah • Segmentation methods of the Insight Toolkit Lydia Ng, Allen Brain Institute • Registration methods of the Insight Toolkit Julien Jomier, Kitware, Inc. – Chapel Hill Office • Image IO using the Insight Toolkit • The Image-Guided Surgery Toolkit (http://www.igstk.org) Stephen Aylward, Kitware, Inc. – Chapel Hill Office • Applications of the Insight Toolkit

Expand Description +

Keywords/Phrases

Search In:

Publication Years