Dr. George J. Grevera Profile

Dr. George J. Grevera

Research Assistant Professor at St Joseph's Univ

SPIE Involvement:

Author

Publications (33)

Proceedings Article | 18 March 2016 Paper

Optimal atlas construction through hierarchical image registration

George Grevera, Jayaram Udupa, Dewey Odhner, Drew Torigian

Proceedings Volume 9786, 97862C (2016) https://doi.org/10.1117/12.2217262

KEYWORDS: Image registration, Medicine, Image segmentation, Chest, 3D modeling, Modeling, Brain-machine interfaces, Rigid registration, Computed tomography, Magnetic resonance imaging, Medical imaging, Systems modeling

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Proceedings Article | 17 February 2012 Paper

Automatic anatomy recognition via fuzzy object models

Jayaram Udupa, Dewey Odhner, Alexandre Falcão, Krzysztof Ciesielski, Paulo A. Miranda, Monica Matsumoto, George Grevera, Babak Saboury, Drew Torigian

Proceedings Volume 8316, 831605 (2012) https://doi.org/10.1117/12.911580

KEYWORDS: Fuzzy logic, Data modeling, Image segmentation, Ferroelectric LCDs, Abdomen, Radiology, Detection and tracking algorithms, Object recognition, Medical imaging, Mathematical modeling

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Proceedings Article | 2 March 2011 Paper

Fuzzy object modeling

Jayaram Udupa, Dewey Odhner, Alexandre Falcao, Krzysztof Ciesielski, Paulo A. Miranda, Pavithra Vaideeswaran, Shipra Mishra, George Grevera, Babak Saboury, Drew Torigian

Proceedings Volume 7964, 79640B (2011) https://doi.org/10.1117/12.878273

KEYWORDS: Fuzzy logic, Data modeling, Image segmentation, Radiology, Binary data, Mathematical modeling, Image processing, Statistical analysis, 3D modeling, Visualization

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Proceedings Article | 30 October 2009 Paper

CAVASS: a framework for medical imaging applications

George Grevera, Jayaram Udupa, Dewey Odhner

Proceedings Volume 7497, 74971D (2009) https://doi.org/10.1117/12.851180

KEYWORDS: Human-machine interfaces, Image processing, Visualization, Binary data, Image segmentation, Volume rendering, Medical imaging, Glasses, Surgery, Image registration

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Proceedings Article | 27 March 2009 Paper

Linear time algorithms for exact distance transform: elaboration on Maurer et al. algorithm

Krzysztof Ciesielski, Jayaram Udupa, Xinjian Chen, George Grevera

Proceedings Volume 7259, 72592T (2009) https://doi.org/10.1117/12.811010

KEYWORDS: Fourier transforms, Binary data, Bismuth, Algorithms, Image processing, Medical imaging, Gold, Image segmentation, 3D image processing, Distance measurement

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Proceedings Article | 13 March 2009 Paper

Using CAVASS as the basis for imaging applications

George Grevera, Jayaram Udupa, Dewey Odhner

Proceedings Volume 7264, 72640M (2009) https://doi.org/10.1117/12.812232

KEYWORDS: Human-machine interfaces, Image processing, Visualization, Surgery, Binary data, Operating systems, Computing systems, C++, Visual analytics, Medical imaging

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Proceedings Article | 17 March 2008 Paper

The architecture and performance of CAVASS

George Grevera, Jayaram Udupa, Dewey Odhner, Ying Zhuge, Andre Souza

Proceedings Volume 6918, 691833 (2008) https://doi.org/10.1117/12.773108

KEYWORDS: Surgery, Image processing, Visualization, Human-machine interfaces, Medical imaging, Binary data, Volume rendering, Software development, Visual analytics, C++

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Proceedings Article | 22 March 2007 Paper

CAVASS: a computer-assisted visualization and analysis software system - image processing aspects

Jayaram Udupa, George Grevera, Dewey Odhner, Ying Zhuge, Andre Souza, Shipra Mishra, Tad Iwanaga

Proceedings Volume 6509, 65091V (2007) https://doi.org/10.1117/12.709841

KEYWORDS: Image processing, Surgery, Visualization, Software development, Image segmentation, Medical imaging, 3D image processing, Visual analytics, Human-machine interfaces, Java

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The development of the concepts within 3DVIEWNIX and of the software system 3DVIEWNIX itself dates back to the 1970s. Since then, a series of software packages for Computer Assisted Visualization and Analysis (CAVA) of images came out from our group, 3DVIEWNIX released in 1993, being the most recent, and all were distributed with source code. CAVASS, an open source system, is the latest in this series, and represents the next major incarnation of 3DVIEWNIX. It incorporates four groups of operations: IMAGE PROCESSING (including ROI, interpolation, filtering, segmentation, registration, morphological, and algebraic operations), VISUALIZATION (including slice display, reslicing, MIP, surface rendering, and volume rendering), MANIPULATION (for modifying structures and surgery simulation), ANALYSIS (various ways of extracting quantitative information). CAVASS is designed to work on all platforms. Its key features are: (1) most major CAVA operations incorporated; (2) very efficient algorithms and their highly efficient implementations; (3) parallelized algorithms for computationally intensive operations; (4) parallel implementation via distributed computing on a cluster of PCs; (5) interface to other systems such as CAD/CAM software, ITK, and statistical packages; (6) easy to use GUI. In this paper, we focus on the image processing operations and compare the performance of CAVASS with that of ITK. Our conclusions based on assessing performance by utilizing a regular (6 MB), large (241 MB), and a super (873 MB) 3D image data set are as follows: CAVASS is considerably more efficient than ITK, especially in those operations which are computationally intensive. It can handle considerably larger data sets than ITK. It is easy and ready to use in applications since it provides an easy to use GUI. The users can easily build a cluster from ordinary inexpensive PCs and reap the full power of CAVASS inexpensively compared to expensive multiprocessing systems which are less efficient for CAVA operations.

Proceedings Article | 21 March 2007 Paper

Introducing CAVASS: a Computer-Assisted Visualization and Analysis Software System

George Grevera, Jayaram Udupa, Dewey Odhner, Ying Zhuge, Andre Souza, Tad Iwanaga, Shipra Mishra

Proceedings Volume 6516, 651608 (2007) https://doi.org/10.1117/12.709725

KEYWORDS: Volume rendering, Visualization, Visual analytics, Image processing, Human-machine interfaces, Image segmentation, Medical imaging, 3D image processing, Binary data, Computing systems

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Proceedings Article | 21 March 2007 Paper

CAVASS: a computer assisted visualization and analysis software system - visualization aspects

George Grevera, Jayaram Udupa, Dewey Odhner, Ying Zhuge, Andre Souza, Tad Iwanaga, Shipra Mishra

Proceedings Volume 6509, 650904 (2007) https://doi.org/10.1117/12.711170

KEYWORDS: Visualization, Volume rendering, Visual analytics, Image processing, Medical imaging, Magnetic resonance imaging, Computing systems, Surgery, Image segmentation, Standards development

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Proceedings Article | 15 March 2006 Paper

Iterative live wire and live snake: new user-steered 3D image segmentation paradigms

Andre Souza, Jayaram Udupa, George Grevera, Yi Sun, Dewey Odhner, Neeti Suri, Mitchell Schnall

Proceedings Volume 6144, 61443N (2006) https://doi.org/10.1117/12.651333

KEYWORDS: Image segmentation, 3D image processing, Breast, Medical imaging, Image processing, 3D modeling, Magnetic resonance imaging, Radiology, 3D magnetic resonance imaging, Data modeling

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Proceedings Article | 12 April 2005 Paper

T-shell rendering and manipulation

George Grevera, Jayaram Udupa, Dewey Odhner

Proceedings Volume 5744, (2005) https://doi.org/10.1117/12.596434

KEYWORDS: Visualization, OpenGL, Image segmentation, Volume rendering, Algorithm development, Binary data, Chemical elements, Video, Image visualization, Ultrafast phenomena

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Proceedings Article | 5 May 2004 Paper

GMIP: generalized maximum intensity projection

George Grevera, Jayaram Udupa

Proceedings Volume 5367, (2004) https://doi.org/10.1117/12.535594

KEYWORDS: Volume rendering, Magnetic resonance imaging, Visualization, Angiography, Chest, Volume visualization, Image processing, Bone, Breast, Tissues

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Proceedings Article | 15 May 2003 Paper

Alignment of multimodality, 2D, and 3D breast images

George Grevera, Jayaram Udupa

Proceedings Volume 5032, (2003) https://doi.org/10.1117/12.481405

KEYWORDS: Breast, Image registration, Magnetic resonance imaging, Positron emission tomography, Ultrasonography, Digital mammography, 3D image processing, Image fusion, Image segmentation, Medical imaging

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Proceedings Article | 17 May 2002 Paper

Area of and volume enclosed by digital and triangulated surfaces

Ingela Nystroem, Jayaram Udupa, George Grevera, Bruce Hirsch

Proceedings Volume 4681, (2002) https://doi.org/10.1117/12.466977

KEYWORDS: Bone, Visualization, Medical imaging, Head, Skull, Surgery, Detection and tracking algorithms, Digital imaging, Binary data, 3D image processing

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Proceedings Article | 9 May 2002 Paper

Methodology for evaluating image-segmentation algorithms

Jayaram Udupa, Vicki LaBlanc, Hilary Schmidt, Celina Imielinska, Punam Saha, George Grevera, Ying Zhuge, L. Currie, Pat Molholt, Yinpeng Jin

Proceedings Volume 4684, (2002) https://doi.org/10.1117/12.467166

KEYWORDS: Image segmentation, Fuzzy logic, Detection and tracking algorithms, Image processing algorithms and systems, Binary data, Tissues, Brain, Image processing, Surgery, Algorithm development

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Proceedings Article | 28 May 2001 Paper

T-shell rendering

George Grevera, Jayaram Udupa, Dewey Odhner

Proceedings Volume 4319, (2001) https://doi.org/10.1117/12.428082

KEYWORDS: Visualization, Volume rendering, Opacity, Sun, OpenGL, Chemical elements, Raster graphics, Detection and tracking algorithms, Volume visualization, Binary data

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Proceedings Article | 18 April 2000 Paper

Volume rendering of medical image data via hardware and in software

George Grevera, Jayaram Udupa, Dewey Odhner

Proceedings Volume 3976, (2000) https://doi.org/10.1117/12.383031

KEYWORDS: Volume rendering, Visualization, Opacity, Medical imaging, Head, OpenGL, Image quality, Image processing, Volume visualization, Image visualization

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Proceedings Article | 18 July 1999 Paper

Replacing film with PACS: work shifting and lack of automation

Steven Horii, Harold Kundel, J. Bruce Kneeland, Regina Redfern, Calvin Nodine, Deborah Arnold, Megan Phelan, George Grevera, Inna Brikman

Proceedings Volume 3662, (1999) https://doi.org/10.1117/12.352761

KEYWORDS: Picture Archiving and Communication System, Radiology, Image processing, Surgery, Diagnostics, Ultrasonography, Chromium, Printing, Radiography, Medical research

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Proceedings Article | 26 May 1999 Paper

Order-of-magnitude faster isosurface rendering in software on a PC than using dedicated general-purpose rendering hardware

George Grevera, Jayaram Udupa, Dewey Odhner

Proceedings Volume 3658, (1999) https://doi.org/10.1117/12.349431

KEYWORDS: OpenGL, Visualization, Sun, Skull, Image visualization, Image segmentation, Medical imaging, Silicon, Fuzzy logic, Detection and tracking algorithms

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Proceedings Article | 13 July 1998 Paper

Prototype controls for a plain radiography workstation

Steven Horii, George Grevera, Eric Feingold, Harold Kundel, Reuben Mezrich, Calvin Nodine, Curtis Langlotz, Regina Redfern, Jill Muck, Megan Phelan, Steven Scoleri

Proceedings Volume 3339, (1998) https://doi.org/10.1117/12.319822

KEYWORDS: Control systems, Radiography, Prototyping, Picture Archiving and Communication System, Chest, Sun, Visualization, Chromium, Eye, Microsystems

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Proceedings Article | 26 June 1998 Paper

Task-specific evaluation of 3D image interpolation techniques

George Grevera, Jayaram Udupa, Yukio Miki

Proceedings Volume 3335, (1998) https://doi.org/10.1117/12.312512

KEYWORDS: Silicon, Image interpolation, Medical imaging, 3D image processing, Image processing, Statistical analysis, Binary data, Fuzzy logic, Imaging systems, Brain

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Proceedings Article | 22 May 1997 Paper

Web-based radiology applications for clinicians and radiologists

Eric Feingold, George Grevera, Reuben Mezrich, Steven Horii, Satjeet Khalsa, Le Phan

Proceedings Volume 3035, (1997) https://doi.org/10.1117/12.274630

KEYWORDS: Databases, Image processing, Chromium, Radiology, Computed tomography, Diagnostics, Image storage, Picture Archiving and Communication System, Zoom lenses, Scanners

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Proceedings Article | 22 May 1997 Paper

What do we need to advance PACS workstations: a critical review with suggestions

Steven Horii, Harold Kundel, Eric Feingold, George Grevera, Calvin Nodine, Curtis Langlotz, Reuben Mezrich, Regina Redfern, Jill Muck

Proceedings Volume 3035, (1997) https://doi.org/10.1117/12.274562

KEYWORDS: Picture Archiving and Communication System, Radiology, Medical imaging, Manufacturing, Control systems, System integration, Human-machine interfaces, Diagnostics, Computing systems, Image processing

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Proceedings Article | 7 May 1997 Paper

Objective comparison of interpolation methods

George Grevera, Jayaram Udupa

Proceedings Volume 3031, (1997) https://doi.org/10.1117/12.273885

KEYWORDS: Binary data, 3D image processing, Data acquisition, Image segmentation, Statistical analysis, Magnetic resonance imaging, Visualization, Brain, Head, Image processing

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Proceedings Article | 1 May 1996 Paper

Implementing desktop image access of GI images

George Grevera, Eric Feingold, Steven Horii, Igor Laufer

Proceedings Volume 2711, (1996) https://doi.org/10.1117/12.239254

KEYWORDS: Digital imaging, Image processing, Computing systems, Radiology, Fluoroscopy, Image storage, Analog electronics, Telecommunications, Sun, Image filtering

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Proceedings Article | 1 May 1996 Paper

PACS workstation functions: usage differences between radiologists and MICU physicians

Steven Horii, Eric Feingold, Harold Kundel, Calvin Nodine, Curtis Langlotz, Regina Redfern, George Grevera, Inna Brikman, Jill Muck

Proceedings Volume 2711, (1996) https://doi.org/10.1117/12.239257

KEYWORDS: Chromium, Control systems, Radiography, Chest, Picture Archiving and Communication System, Zoom lenses, Diagnostics, Radiology, Medical imaging, Sun

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Proceedings Article | 1 May 1996 Paper

WWW to DICOM interface

George Grevera, Eric Feingold, Steven Horii

Proceedings Volume 2711, (1996) https://doi.org/10.1117/12.239238

KEYWORDS: Picture Archiving and Communication System, Radiology, Image processing, Databases, Diagnostics, Standards development, Image retrieval, System integration, Sun, Spine

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Proceedings Article | 16 April 1996 Paper

Deformation of n-dimensional digital Jordan surfaces

George Grevera, Jayaram Udupa

Proceedings Volume 2710, (1996) https://doi.org/10.1117/12.237964

KEYWORDS: Neodymium, Algorithms, Image segmentation, Data modeling, Surgery, Medical imaging, 3D modeling, Medical research, Visual process modeling, Visual analytics

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Active contour models have become popular recently especially in medical image segmentation research and in the modeling of deformable structures. There are a number of theoretical, computational, and operational advantages to treating the boundary as a digital entity and defining deformations digitally on the digital representation. Nevertheless, this does not seem to have been pursued in the literature. A significant body of knowledge exists in the literature on the theory and algorithms related to nD, oriented, closed, connected, digital surfaces. In this paper we examine how this knowledge can be utilized to extend active contour models to nD digital surfaces. We present an algorithm for deforming nD, oriented, closed, connected digital surfaces into nD, oriented, closed, connected digital surfaces. The algorithm uses a data structure which we call a random insertion/deletion list. It contains spatial elements (spels) that constitute the immediate interior (II) of the surface as well as information that establishes the relationship of the spels to the surface elements (surfels). (In our digital surface model, the surfels are one lower dimensional than the spels. For example, in 3D, the spel is a voxel and a surfel is a square representing the voxel face). All deformations are realized essentially by adding/deleting spels to/from the data structure. Our results indicate that it is possible to model surfaces digitally and that given an nD, oriented, closed, connected, digital surface, we can deform this surface using local operations only to produce an nD, oriented, closed, digital surface. We also describe an algorithm and data structures to implement this model efficiently. Furthermore, if we allow more global tests, we can also insure that connectedness of the surface is insured as well. We conclude that the extensively studied digital surface models are appropriate for representing deformable objects also. Because of the finite (and small number of) local configurations of surfels and spels, these models offer efficient deformation computation as has been repeatedly demonstrated in the past for a variety of visualization and analysis operations. We demonstrate that we can deform the surface in such ways that maintain orientation and closure using only local checks and we can also insure connectedness at the expense of global checks.

Proceedings Article | 15 April 1996 Paper

Shape-based interpolation of nD gray scenes

George Grevera, Jayaram Udupa

Proceedings Volume 2707, (1996) https://doi.org/10.1117/12.238438

KEYWORDS: Binary data, Information operations, Silicon, Data acquisition, Image processing, Lithium, Medical imaging, Neodymium, Visualization, Data conversion

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Proceedings Article | 15 April 1996 Paper

Shape-based image compression

George Grevera, Jayaram Udupa

Proceedings Volume 2707, (1996) https://doi.org/10.1117/12.238457

KEYWORDS: Image compression, Computer programming, Binary data, Medical imaging, Neodymium, Chromium, Data compression, Image interpolation, Digital imaging, Data acquisition

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As medical image data are acquired at higher spatial, gray-scale, and temporal resolution, with increasing image dimensionality and vectorial components per image element, the need to be able to compress them becomes increasingly important, especially for the practical utilization of PACS. Further, a compression method that allows an efficient in-memory representation would be very useful for those processing situations in which the non-compressed data are beyond RAM resources. Consider an n-dimensional (nD) scene intensity function (m- valued) as a digital surface in an (n plus m)D space as described below. The approach leads to a spectrum of lossless and lossy compression methods. For a 2D, scalar valued (m equals 1) scene S, for example, the 3D digital surface representing S is simply the graph of the scene intensity function. The first two coordinates of points on the surface represent the coordinates of a pixel in S and the third coordinate represents the pixel's intensity. In this example, if m equals 2, then the third and the fourth coordinates of the points in the 4D surface represent the two pixel values. The digital surfaces obtained from scenes via this process (referred to as lifting as described below) have certain distinct topological properties not shared by general digital surfaces (for example, they do not enclose holes). These properties allow us to encode them elegantly. For example, the entire surface (for any finite n greater than 0, m greater than 0) can be represented by a Hamiltonian path of surface elements in the graph representing the surface. This path is chain-encoded facilitated by the small number of possible configurations and orientations of adjacent surface elements. Our (very) preliminary results indicate lossless compression ratios of 4.6:1 for CT slices and 1.7:1 for CR scalar-valued scenes (n equals 2, m equals 1) representing 2D scenes. Our preliminary implementation uses simple chain codes that do not exploit the repetitive patterns in the Hamiltonian path. When this is done, and the implementation is extended to scenes with n plus m greater than 3, we expect a higher degree of compression due to the full exploitation of the spatio-temporal and vectorial component coherence. This paper opens a new direction for data compression not taken in previous research. It seems to capture regional information about the uniformity of the intensity distribution better than other methods. It also extends the current shape-based methods used in image interpolation to include compression.

Proceedings Article | 9 September 1994 Paper

Fuzzy objects and their boundaries

Jayaram Udupa, Supun Samarasekera, Kootala Venugopal, George Grevera

Proceedings Volume 2359, (1994) https://doi.org/10.1117/12.185205

KEYWORDS: Fuzzy logic, Visualization, Surgery, Visual analytics, Algorithm development, Image segmentation, Volume rendering, Binary data, Image processing algorithms and systems, Biomedical optics

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Proceedings Article | 1 May 1994 Paper

Shape-based interpolation of multidimensional grey-level images

George Grevera, Jayaram Udupa

Proceedings Volume 2164, (1994) https://doi.org/10.1117/12.174002

KEYWORDS: Binary data, Transform theory, Medical imaging, Data conversion, Image segmentation, Image processing, Data acquisition, Data storage, Natural surfaces, Skull

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Showing 5 of 33 publications

Conference Committee Involvement (16)