Web-based visualization for 3D data in archaeology : The ADS 3D viewer

The solid geometry of archaeological deposits is fundamental to the interpretation of their chronological sequence. However, such stratigraphic sequences are generally viewed as static two-dimensional diagrammatic representations which are difficult to manipulate or to relate to real layers. The ADS 3D Viewer is a web-based resource for the management and analysis of archaeological data. The viewer was developed to take advantage of recent developments in web technology, namely the adoption of WebGL (Web Graphics Library) by current web browsers. The ADS 3D Viewer combines the potential of the 3D Heritage Online Presenter (3DHOP), a software package for the web-based visualization of 3D geometries, with the infrastructure of the Archaeology Data Service (ADS) repository, in the attempt to create a platform for the visualization and analysis of 3D data archived by the ADS. Two versions of the viewer have been developed to answer the needs of different users. The first version, the Object Level 3D Viewer, was implemented to extend the browsing capability of ADS project archives by enabling the visualization of single 3D models. The second version, the Stratigraphy 3D Viewer, is an extension which allows the exploration of a specific kind of aggregated data: the multiple layers of an archaeological stratigraphic sequence. This allows those unable to participate directly in the fieldwork to access, analyse and re-interpret the archaeological context remotely. This has the potential to transform the discipline, allowing inter-disciplinary, cross-border and ‘at-distance’ collaborative workflows, and enabling easier access to and analysis of archaeological data

09251 Abstracts Collection -- Scientific Visualization

From 06-14-2009 to 06-19-2009, the Dagstuhl Seminar 09251 ``Scientific Visualization \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, over 50 international participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general

Topology Preserving Simplification of 2D Non-Manifold Meshes with Embedded Structures

International audienceMesh simplification has received tremendous attention over the past years. Most of the previous works deal with a proper choice of error measures to guide the simplification. Preserving the topological characteristics of the mesh and possibly of data attached to the mesh is a more recent topic, the present paper is about.We introduce a new topology preserving simplification algorithm for triangular meshes, possibly non-manifold, with embedded polylines. In this context embedded means that the edges of the polylines are also edges of the mesh. The paper introduces a robust test to detect if the collapse of an edge in the mesh modifies either the topology of the mesh or the topology of the embedded polylines. This validity test is derived using combinatorial topology results. More precisely we define a so-called extended complex from the input mesh and the embedded polylines. We show that if an edge collapse of the mesh preserves the topology of this extended complex, then it also preserves both the topology of the mesh and the embedded polylines. Our validity test can be used for any 2-complex mesh, including non-manifold triangular meshes. It can be combined with any previously introduced error measure. Implementation of this validity test is described. We demonstrate the power and versatility of our method with scientific data sets from neuroscience, geology and CAD/CAM models from mechanical engineering

Techniques and algorithms for immersive and interactive visualization of large datasets

Advances in computing power have made it possible for scientists to perform atomistic simulations of material systems that range in size, from a few hundred thousand atoms to one billion atoms. An immersive and interactive walkthrough of such datasets is an ideal method for exploring and understanding the complex material processes in these simulations. However rendering such large datasets at interactive frame rates is a major challenge. A scalable visualization platform is developed that is scalable and allows interactive exploration in an immersive, virtual environment. The system uses an octree based data management system that forms the core of the application. This reduces the amount of data sent to the pipeline without a per-atom analysis. Secondary algorithms and techniques such as modified occlusion culling, multiresolution rendering and distributed computing are employed to further speed up the rendering process. The resulting system is highly scalable and is capable of visualizing large molecular systems at interactive frame rates on dual processor SGI Onyx2 with an InfinteReality2 graphics pipeline

Histopathological image analysis : a review

Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe

Automated Segmentation of Cerebral Aneurysm Using a Novel Statistical Multiresolution Approach

Cerebral Aneurysm (CA) is a vascular disease that threatens the lives of many adults. It a ects almost 1:5 - 5% of the general population. Sub- Arachnoid Hemorrhage (SAH), resulted by a ruptured CA, has high rates of morbidity and mortality. Therefore, radiologists aim to detect it and diagnose it at an early stage, by analyzing the medical images, to prevent or reduce its damages. The analysis process is traditionally done manually. However, with the emerging of the technology, Computer-Aided Diagnosis (CAD) algorithms are adopted in the clinics to overcome the traditional process disadvantages, as the dependency of the radiologist's experience, the inter and intra observation variability, the increase in the probability of error which increases consequently with the growing number of medical images to be analyzed, and the artifacts added by the medical images' acquisition methods (i.e., MRA, CTA, PET, RA, etc.) which impedes the radiologist' s work. Due to the aforementioned reasons, many research works propose di erent segmentation approaches to automate the analysis process of detecting a CA using complementary segmentation techniques; but due to the challenging task of developing a robust reproducible reliable algorithm to detect CA regardless of its shape, size, and location from a variety of the acquisition methods, a diversity of proposed and developed approaches exist which still su er from some limitations. This thesis aims to contribute in this research area by adopting two promising techniques based on the multiresolution and statistical approaches in the Two-Dimensional (2D) domain. The rst technique is the Contourlet Transform (CT), which empowers the segmentation by extracting features not apparent in the normal image scale. While the second technique is the Hidden Markov Random Field model with Expectation Maximization (HMRF-EM), which segments the image based on the relationship of the neighboring pixels in the contourlet domain. The developed algorithm reveals promising results on the four tested Three- Dimensional Rotational Angiography (3D RA) datasets, where an objective and a subjective evaluation are carried out. For the objective evaluation, six performance metrics are adopted which are: accuracy, Dice Similarity Index (DSI), False Positive Ratio (FPR), False Negative Ratio (FNR), speci city, and sensitivity. As for the subjective evaluation, one expert and four observers with some medical background are involved to assess the segmentation visually. Both evaluations compare the segmented volumes against the ground truth data

A distributed and energy‑efficient KNN for EEG classification with dynamic money‑saving policy in heterogeneous clusters

Universidad de Granada/CBUASpanish Ministry of Science, Innovation, and Universities under Grants PGC2018-098813-B-C31,PID2022-137461NB-C32ERDF fund. Funding for open access charge: University of Granada/ CBU

TOM: totally ordered mesh. A multiresolution data structure for time-critical graphics applications

Tridimensional interactive applications are confronted to situations where very large databases have to be animated, transmitted and displayed in very short bounded times. As it is generally impossible to handle the complete graphics description while meeting timing constraint, techniques enabling the extraction and manipulation of a significant part of the geometric database have been the focus of many research works in the field of computer graphics. Multiresolution representations of 3D models provide access to 3D objects at arbitrary resolutions while minimizing appearance degradation. Several kinds of data structures have been recently proposed for dealing with polygonal or parametric representations, but where not generally optimized for time-critical applications. We describe the TOM (Totally Ordered Mesh), a multiresolution triangle mesh structure tailored to the support of time-critical adaptive rendering. The structure grants high speed access to the continuous levels of detail of a mesh and allows very fast traversal of the list of triangles at arbitrary resolution so that bottlenecks in the graphic pipeline are avoided. Moreover, and without specific compression, the memory footprint of the TOM is small (about 108% of the single resolution object in face-vertex form) so that large scenes can be effectively handled. The TOM structure also supports storage of per vertex (or per corner of triangle) attributes such as colors, normals, texture coordinates or dynamic properties. Implementation details are presented along with the results of tests for memory needs, approximation quality, timing and efficacy