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

Grevera, George J.; Udupa, Jayaram K.; Odhner, Dewey; Zhuge, Ying; Souza, Alex Júnior Souza de; Iwanaga, Tad; Mishra, Saurabh

doi:10.1117/12.711170

Cited by 5 publications

(3 citation statements)

References 80 publications

(87 reference statements)

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“…The software design aspects of CAVASS are described in detail in a companion paper in these proceedings [60]. The aspects of visualization are covered in another paper [59]. In the present paper, we focus mainly on the image processing aspects (E1) indicated by the first of the four CAVA functions in Figure 1.…”

Section: Methodsmentioning

confidence: 99%

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

Udupa

Grevera

Odhner

et al. 2007

Medical Imaging 2007: Visualization and Image-Guided Procedures

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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.

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Section: Methodsmentioning

confidence: 99%

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

Udupa

Grevera

Odhner

et al. 2007

Medical Imaging 2007: Visualization and Image-Guided Procedures

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“…Firstly, image registration was conducted on the OCT images using CAVASS [11]. The image of the first time point is used as the reference image and other images are registered to it via a rigid transformation.…”

Section: Pre-processingmentioning

confidence: 99%

3D choroid neovascularization growth prediction based on reaction-diffusion model

et al. 2016

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Choroid neovascularization (CNV) is a kind of pathology from the choroid and CNV-related disease is one important cause of vision loss. It is desirable to predict the CNV growth rate so that appropriate treatment can be planned. In this paper, we seek to find a method to predict the growth of CNV based on 3D longitudinal Optical Coherence Tomography (OCT) images. A reaction-diffusion model is proposed for prediction. The method consists of four phases: preprocessing, meshing, CNV growth modeling and prediction. We not only apply the reaction-diffusion model to the disease region, but also take the surrounding tissues into consideration including outer retinal layer, inner retinal layer and choroid layer. The diffusion in these tissues is considered as isotropic. The finite-element-method (FEM) is used to solve the partial differential equations (PDE) in the diffusion model. The curve of CNV growth with treatment are fitted and then we can predict the CNV status in a future time point. The preliminary results demonstrated that our proposed method is accurate and the validity and feasibility of our model is obvious.

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“…CAVASS can also read and write other common 2D image formats such as TIFF [9], GIF [10], JPEG [11], VTK [12,13], PNG [14], STL (Stereo Lithography, a common CAD/CAM format) [15], and the NETPBM format family [16] as well. Previously, we described and evaluated the image processing [17] and visualization [18] capabilities of CAVASS. We now describe the general software architecture of CAVASS so one may quickly use it as the basis for one's own applications.…”

Section: Introductionmentioning

confidence: 99%

CAVASS: a framework for medical imaging applications

2009

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Computer Aided Visualization and Analysis Software System (CAVASS) is an open-source software system that is being developed by the Medical Image Processing Group (MIPG) at the University of Pennsylvania. CAVASS is freely available, open source, integrated with popular toolkits, and runs on Windows, Unix, Linux, and Mac OS. It includes extremely efficient of the most commonly used image display, manipulation, and processing operations. Parallel implementations of computationally demanding tasks such as deformable registration are provided as well using the inexpensive COW (Cluster of Workstations) model. CAVASS also seamlessly integrates and interfaces with ITK and provides a graphical user interface for ITK as well. CAVASS can easily interface with a PACS by directly reading and writing medical images in the industry standard DICOM format and can also input and output other common image formats as well. We describe the key features, general software architecture, interface with ITK, parallel architecture, and the CAVASS build and test environment. New stereo rendering capabilities are described as well.

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

Cited by 5 publications

References 80 publications

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

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

3D choroid neovascularization growth prediction based on reaction-diffusion model

CAVASS: a framework for medical imaging applications

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