CAVASS: A Computer-Assisted Visualization and Analysis Software System
George J. Grevera,George J. Grevera,Jayaram K. Udupa,Dewey Odhner,Ying Zhuge,Andre Souza,Tad Iwanaga,Shipra Mishra +7 more
TL;DR: CAVASS is directed at the visualization, processing, and analysis of 3-dimensional and higher-dimensional medical imagery, so support for digital imaging and communication in medicine data and the efficient implementation of algorithms is given paramount importance.
read more
Abstract: The Medical Image Processing Group at the University of Pennsylvania has been developing (and distributing with source code) medical image analysis and visualization software systems for a long period of time. Our most recent system, 3DVIEWNIX, was first released in 1993. Since that time, a number of significant advancements have taken place with regard to computer platforms and operating systems, networking capability, the rise of parallel processing standards, and the development of open-source toolkits. The development of CAVASS by our group is the next generation of 3DVIEWNIX. CAVASS will be freely available and open source, and it is integrated with toolkits such as Insight Toolkit and Visualization Toolkit. CAVASS runs on Windows, Unix, Linux, and Mac but shares a single code base. Rather than requiring expensive multiprocessor systems, it seamlessly provides for parallel processing via inexpensive clusters of work stations for more time-consuming algorithms. Most importantly, CAVASS is directed at the visualization, processing, and analysis of 3-dimensional and higher-dimensional medical imagery, so support for digital imaging and communication in medicine data and the efficient implementation of algorithms is given paramount importance.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Chest Fat Quantification via CT Based on Standardized Anatomy Space in Adult Lung Transplant Candidates.
Yubing Tong,Jayaram K. Udupa,Drew A. Torigian,Dewey Odhner,Caiyun Wu,Gargi Pednekar,Scott M. Palmer,Anna Rozenshtein,Melissa A. Shirk,John D. Newell,Mary K. Porteous,Joshua M. Diamond,Jason D. Christie,David J. Lederer +13 more
TL;DR: An approach to chest fat quantification and quality assessment based on a recently formulated concept of standardized anatomic space (SAS) is presented and demonstrates a new way of optimally selecting slices whose measurements may be used as markers of similar measurements made on the whole chest volume.
AAR-RT - A system for auto-contouring organs at risk on CT images for radiation therapy planning: Principles, design, and large-scale evaluation on head-and-neck and thoracic cancer cases.
Xingyu Wu,Jayaram K. Udupa,Yubing Tong,Dewey Odhner,Gargi Pednekar,Charles B. Simone,David J. McLaughlin,Chavanon Apinorasethkul,Ontida Apinorasethkul,John N. Lukens,Dimitris Mihailidis,Geraldine Shammo,Paul A. James,Akhil Tiwari,Lisa Wojtowicz,Joseph Camaratta,Drew A. Torigian +16 more
TL;DR: This paper extended the previous body‐wide Automatic Anatomy Recognition (AAR) framework to RT planning of OARs in the head and neck (H&N) and thoracic body regions, and devised a method to find an optimal hierarchy for each body region.
33
Image Quality and Segmentation.
Gargi Pednekar,Jayaram K. Udupa,David J. McLaughlin,Xingyu Wu,Yubing Tong,Charles B. Simone,Joseph Camaratta,Drew A. Torigian +7 more
- 01 Feb 2018
TL;DR: A set of key quality criteria that influence segmentation (global and regional): posture deviations, image noise, beam hardening artifacts (streak artifacts), shape distortion, presence of pathology, object intensity deviation, and object contrast are devised.
30
Linear Time Algorithms for Exact Distance Transform
TL;DR: The theoretical and practical version of the signed distance transform algorithm, GBDT, returns the exact value of the distance from the geometrically defined object boundary, and it is proved that this algorithm can be used to find, in linear time, the largest possible distance between any two of its elements.
Laser surface texturing of tool steel: textured surfaces quality evaluation
TL;DR: In this article, the laser surface texturing of tool steel of type 90MnCrV8 has been conducted on the 5-axis highly dynamic laser precision machining centre Lasertec 80 Shape equipped with the nano-second pulsed ytterbium fiber laser and CNC system Siemens 840 D.
References
Marching cubes: A high resolution 3D surface construction algorithm
William E. Lorensen,Harvey E. Cline +1 more
- 01 Aug 1987
TL;DR: In this paper, a divide-and-conquer approach is used to generate inter-slice connectivity, and then a case table is created to define triangle topology using linear interpolation.
Scale-space and edge detection using anisotropic diffusion
Pietro Perona,Jitendra Malik +1 more
TL;DR: A new definition of scale-space is suggested, and a class of algorithms used to realize a diffusion process is introduced, chosen to vary spatially in such a way as to encourage intra Region smoothing rather than interregion smoothing.
Fast approximate energy minimization via graph cuts
TL;DR: This work presents two algorithms based on graph cuts that efficiently find a local minimum with respect to two types of large moves, namely expansion moves and swap moves that allow important cases of discontinuity preserving energies.
Fast approximate energy minimization via graph cuts
Yuri Boykov,Olga Veksler,Ramin Zabih +2 more
- 01 Jan 1999
TL;DR: This paper proposes two algorithms that use graph cuts to compute a local minimum even when very large moves are allowed, and generates a labeling such that there is no expansion move that decreases the energy.
Current methods in medical image segmentation.
TL;DR: A critical appraisal of the current status of semi-automated and automated methods for the segmentation of anatomical medical images is presented, with an emphasis on the advantages and disadvantages of these methods for medical imaging applications.
2.5K