Feed-forward volume rendering algorithm for moderately parallel MIMD machines

Algorithms for direct volume rendering on parallel and vector processors are investigated. Volumes are transformed efficiently on parallel processors by dividing the data into slices and beams of voxels. Equal sized sets of slices along one axis are distributed to processors. Parallelism is achieved at two levels. Because each slice can be transformed independently of others, processors transform their assigned slices with no communication, thus providing maximum possible parallelism at the first level. Within each slice, consecutive beams are incrementally transformed using coherency in the transformation computation. Also, coherency across slices can be exploited to further enhance performance. This coherency yields the second level of parallelism through the use of the vector processing or pipelining. Other ongoing efforts include investigations into image reconstruction techniques, load balancing strategies, and improving performance

CAVASS: A Computer-Assisted Visualization and Analysis Software System

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

Three--dimensional medical imaging: Algorithms and computer systems

This paper presents an introduction to the field of three-dimensional medical imaging It presents medical imaging terms and concepts, summarizes the basic operations performed in three-dimensional medical imaging, and describes sample algorithms for accomplishing these operations. The paper contains a synopsis of the architectures and algorithms used in eight machines to render three-dimensional medical images, with particular emphasis paid to their distinctive contributions. It compares the performance of the machines along several dimensions, including image resolution, elapsed time to form an image, imaging algorithms used in the machine, and the degree of parallelism used in the architecture. The paper concludes with general trends for future developments in this field and references on three-dimensional medical imaging

Analysis of (iso)surface reconstructions: Quantitative metrics and methods

Due to sampling processes volumetric data is inherently discrete and most often knowledge of the underlying continuous model is not available. Surface rendering techniques attempt to reconstruct the continuous model, using isosurfaces, from the discrete data. Therefore, it natural to ask how accurate the reconstructed isosurfaces are with respect to the underlying continuous model. A reconstructed isosurface may look impressive when rendered ( photorealism ), but how well does it reflect reality ( physical realism )?;The users of volume visualization packages must be aware of the short-comings of the algorithms used to produce the images so that they may properly interpret, and interact with, what they see. However, very little work has been done to quantify the accuracy of volumetric data reconstructions. Most analysis to date has been qualitative. Qualitative analysis uses simple visual inspection to determine whether characteristics, known to exist in the real world object, are present in the rendered image. Our research suggests metrics and methods for quantifying the physical realism of reconstructed isosurfaces.;Physical realism is a many faceted notion. In fact, a different metric could be defined for each physical property one wishes to consider. We have defined four metrics--Global Surface Area Preservation (GSAP), Volume Preservation (VP), Point Distance Preservation (PDP), and Isovalue Preservation (IVP). We present experimental results for each of these metrics and discuss their validity with respect to those results.;We also present the Reconstruction Quantification (sub)System (RQS). RQS provides a flexible framework for measuring physical realism. This system can be embedded in existing visualization systems with little modification of the system itself. Two types of analysis can be performed; reconstruction analysis and algorithm analysis. Reconstruction analysis allows users to determine the accuracy of individual surface reconstructions. Algorithm analysis, on the other hand, allows developers of visualization systems to determine the efficacy of the visualization system based on several reconstructions

3-D data handling and registration of multiple modality medical images

The many different clinical imaging modalities used in diagnosis and therapy deliver two different types of information: morphological and functional. Clinical interpretation can be assisted and enhanced by combining such information (e.g. superimposition or fusion). The handling of such data needs to be performed in 3-D. Various methods for registration developed by other authors are reviewed and compared. Many of these are based on registering external reference markers, and are cumbersome and present significant problems to both patients and operators. Internal markers have also been used, but these may be very difficult to identify. Alternatively, methods based on the external surface of an object have been developed which eliminate some of the problems associated with the other methods. Thus the methods which have been extended, developed, and described here, are based primarily on the fitting of surfaces, as determined from images obtained from the different modalities to be registered. Annex problems to that of the surface fitting are those of surface detection and display. Some segmentation and surface reconstruction algorithms have been developed to identify the surface to be registered. Surface and volume rendering algorithms have also been implemented to facilitate the display of clinical results. An iterative surface fitting algorithm has been developed based on the minimization of a least squares distance (LSD) function, using the Powell method and alternative minimization algorithms. These algorithms and the qualities of fit so obtained were intercompared. Some modifications were developed to enhance the speed of convergence, to improve the accuracy, and to enhance the display of results during the process of fitting. A common problem with all such methods was found to be the choice of the starting point (the initial transformation parameters) and the avoidance of local minima which often require manual operator intervention. The algorithm was modified to apply a global minimization by using a cumulative distance error in a sequentially terminated process in order to speed up the time of evaluating of each search location. An extension of the algorithm into multi-resolution (scale) space was also implemented. An initial global search is performed at coarse resolution for the 3-D surfaces of both modalities where an appropriate threshold is defined to reject likely mismatch transformations by testing of only a limited subset of surface points. This process is used to define the set of points in the transformation space to be used for the next level of resolution, again with appropriately chosen threshold levels, and continued down to the finest resolution level. All these processes were evaluated using sets of well defined image models. The assessment of this algorithm for 3-D surface registration of data from (3-D) MRI with MRI, MRI with PET, MRI with SPECT, and MRI with CT data is presented, and clinical examples are illustrated and assessed. In the current work, the data from multi-modality imaging of two different types phantom (e.g. Hoffman brain phantom, Jaszczak phantom), thirty routinely imaged patients and volunteer subjects, and ten patients with setting external markers on their head were used to assess and verify 3-D registration. The accuracy of the sequential multi-resolution method obtained by the distance values of 4-10 selected reference points on each data set gave an accuracy of 1.44±0.42 mm for MR-MR, 1.82±0.65 for MR-CT, 2.38±0.88 for MR-PET, and 3.17±1.12 for MR-SPECT registration. The cost of this process was determined to be of the order of 200 seconds (on a Micro-VAX II), although this is highly dependent on some adjustable parameters of the process (e.g. threshold and the size of the geometrical transformation space) by which the accuracy is aimed

Reverse Thinking in Spatial Queries

In recent years, an increasing number of researches are conducted on spatial queries regarding the influence of query objects. Among these queries, reverse k nearest neighbors (RkNN) query is the one studied the most extensively. Reverse k furthest neighbors (RkFN) queries is the natural complement of RkNN queries. RkNN query is introduced to reflect the influence of the query object. Since this representation is intuitive, RkNN query has attracted significant attention among the database community. Later, reverse top-k queries was introduced, and also used extensively to represent influence. In many scenarios, when we consider the influence of an spatial object, reverse thinking is involved. That is, whether an object is influential to another object is depending on how the other object assess this object, other than how this object considers the other object. In this thesis, we study three problems involves reverse thinking. We first study the problem of efficiently computing RkFN queries. We are the first to propose a solution for arbitrary value of k. Based on several interesting observations, we present an efficient algorithm to process the RkFN queries. We also present a rigorous theoretical analysis to study various important aspects of the problem and our algorithm. An extensive experimental study demonstrates that our algorithm outperforms the state-of-the-art algorithm even for k=1. The accuracy of our theoretical analysis is also verified. We then study the problem of selecting set of representative products considering both diversity and coverage based on reverse top-k queries. Since this problem is NP-hard, we employ a greedy algorithm. We adopt MinHash and KMV Synopses to assist set operations. Our experimental study demonstrates the performance of the proposed algorithm. We also study the problem of maximizing spatial influence of facility bundle based on RkNN queries. We are the first to study this problem. We prove its NP-hardness, and propose a branch-and-bound best first search algorithm that greedily select the currently best facility until we get the required number of facilities. We introduce the concept of kNN region. It allows us to avoid redundant calculation with dynamic programming technique. Experiments show that our algorithm is orders of magnitudes better than our baseline algorithm

Segmentação e visualização tridimensional interativa de imagens de ressonancia magnetica

Orientadores: Roberto de Alencar Lotufo, Alexandre Xavier FalcãoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de ComputaçãoMestradoEngenharia de ComputaçãoMestre em Engenharia Elétric

The slicing extent technique for fast ray tracing

A new technique for image generation using ray tracing is introduced. The “Slicing Extent Technique” (SET) partitions object space with slicing planes perpendicular to all three axes. Planes are divided into two dimensional rectangular cells, which contain pointers to nearby objects. Cell size and the space between slices varies, and is determined by the objects’ locations and orientations. Unlike oct-tree and other space-partitioning methods, SET is not primarily concerned with dividing space into mutually exclusive volume elements (‘voxels’) and identifying objects within each voxel. Instead, SET is based on analysis of projections of objects onto slicing planes. In comparison to the existing space subdivision methods for ray tracing, SET avoids tree traversal and exhibit no anomalous behavior. There is no reorganization when new objects arrive. Preprocessing to create slices is inexpensive and produces a finely tuned filter mechanism which supports rapid ray tracing

Hardware-supported cloth rendering

Many computer graphics applications involve rendering humans and their natural surroundings, which inevitably requires displaying textiles. To accurately resemble the appearance of e.g. clothing or furniture, reflection models are needed which are capable of modeling the highly complex reflection effects exhibited by textiles. This thesis focuses on generating realistic high quality images of textiles by developing suitable reflection models and introducing algorithms for illumination computation of cloth surfaces. As efficiency is essential for illumination computation, we additionally place great importance on exploiting graphics hardware to achieve high frame rates. To this end, we present a variety of hardware-accelerated methods to compute the illumination in textile micro geometry. We begin by showing how indirect illumination and shadows can be efficiently accounted for in heightfields, parametric surfaces, and triangle meshes. Using these methods, we can considerably speed up the computation of data structures like tabular bidirectional reflectance distribution functions (BRDFs) and bidirectional texture functions (BTFs), and also efficiently illuminate heightfield geometry and bump maps. Furthermore, we develop two shading models, which account for all important reflection properties exhibited by textiles. While the first model is suited for rendering textiles with general micro geometry, the second, based on volumetric textures, is specially tailored for rendering knitwear. To apply the second model e.g. to the triangle mesh of a garment, we finally introduce a new rendering algorithm for displaying semi-transparent volumetric textures at high interactive rates.Eine Vielzahl von Anwendungen in der Computergraphik schließen auch die Darstellung von Menschen und deren natürlicher Umgebung ein, was zwangsläufig auch die Darstellung von Textilien erfordert. Um beispielsweise das Aussehen von Bekleidung oder Möbeln genau zu erfassen, werden Reflexionsmodelle benötigt, die in der Lage sind, die hochkomplexen Reflexionseffekte von Textilien zu berücksichtigen. Der Schwerpunkt dieser Dissertation liegt in der Generierung qualitativ hochwertiger Bilder von Textilien, was wir durch die Entwicklung geeigneter Reflexionsmodelle und von Algorithmen zur Beleuchtungsberechnung an Stoffoberflächen ermöglichen. Da Effizienz essentiell für die Beleuchtungsberechnung ist, nutzen wir die Möglichkeiten von Graphikhardware aus, um hohe Bildwiederholraten zu erzielen. Hierfür legen wir eine Vielzahl von hardware-beschleunigten Methoden zur Beleuchtungsberechnung der Mikrogeometrie von Textilien vor. Zuerst zeigen wir, wie indirekte Beleuchtung und Schatten effizient in Höhenfeldern, parametrischen Flächen und Dreiecksnetzen berücksichtigt werden können. Mit Hilfe dieser Methoden kann die Berechnung von Datenstrukturen wie tabellarischer bidirectional reflectance distribution functions (BRDFs) und bidirectional texture functions (BTFs) erheblich beschleunigt, sowie die Beleuchtung von Höhenfeld-Geometrie und Bumpmaps effizient errechnet werden.Weiterhin entwickeln wir zwei Reflexionsmodelle, welche alle wichtigen Reflexionseigenschaften berücksichtigen, die Textilien aufweisen. Während das erste Modell sich zur Darstellung von Textilien mit allgemeiner Mikrogeometrie eignet, ist das zweite, welches auf volumetrischen Texturen basiert, speziell auf die Darstellung von Strickwaren zugeschnitten. Um das zweite Modell z.B. auf das Dreiecksnetz eines Bekleidungsstückes anzuwenden führen wir einen neuen Renderingalgorithmus für die Darstellung von semi-transparenten volumetrischen Texturen mit hohen Bildwiederholraten ein