MFA-DVR: Direct Volume Rendering of MFA Models

3D volume rendering is widely used to reveal insightful intrinsic patterns of volumetric datasets across many domains. However, the complex structures and varying scales of volumetric data can make efficiently generating high-quality volume rendering results a challenging task. Multivariate functional approximation (MFA) is a new data model that addresses some of the critical challenges: high-order evaluation of both value and derivative anywhere in the spatial domain, compact representation for large-scale volumetric data, and uniform representation of both structured and unstructured data. In this paper, we present MFA-DVR, the first direct volume rendering pipeline utilizing the MFA model, for both structured and unstructured volumetric datasets. We demonstrate improved rendering quality using MFA-DVR on both synthetic and real datasets through a comparative study. We show that MFA-DVR not only generates more faithful volume rendering than using local filters but also performs faster on high-order interpolations on structured and unstructured datasets. MFA-DVR is implemented in the existing volume rendering pipeline of the Visualization Toolkit (VTK) to be accessible by the scientific visualization community

IMAGE-IN: Interactive web-based multidimensional 3D visualizer for multi-modal microscopy images

Advances in microscopy hardware and storage capabilities lead to increasingly larger multidimensional datasets. The multiple dimensions are commonly associated with space, time, and color channels. Since “seeing is believing”, it is important to have easy access to user-friendly visualization software. Here we present IMAGE-IN, an interactive web-based multidimensional (N-D) viewer designed specifically for confocal laser scanning microscopy (CLSM) and focused ion beam scanning electron microscopy (FIB-SEM) data, with the goal of assisting biologists in their visualization and analysis tasks and promoting digital work-flows. This new visualization platform includes intuitive multidimensional opacity fine-tuning, shading on/off, multiple blending modes for volume viewers, and the ability to handle multichannel volumetric data in volume and surface views. The software accepts a sequence of image files or stacked 3D images as input and offers a variety of viewing options ranging from 3D volume/surface rendering to multiplanar reconstruction approaches. We evaluate the performance by comparing the loading and rendering timings of a heterogeneous dataset of multichannel CLSM and FIB-SEM images on two devices with installed graphic cards, as well as comparing rendered image quality between ClearVolume (the ImageJ open-source desktop viewer), Napari (the Python desktop viewer), Imaris (the closed-source desktop viewer), and our proposed IMAGE-IN web viewer

Estudio y evaluación de métodos de visualización de imágenes biológicas multidimensionales utilizando OpenGL

Las modernas tecnologías de adquisición de imágenes (TAC, RMN, microscopia Confocal, etc.) permiten el registro, no sólo de imágenes tridimensionales, sino de imágenes multidimensionales. Sin embargo, el análisis visual de tales volúmenes de información no es una tarea simple, se requiere de programas de representación gráfica, que oculten la complejidad del sistema de digitalización facilitando el análisis al experto. En este trabajo se han seleccionado para la implementación, análisis y evaluación dos técnicas de representación de imágenes multidimensionales: Proyección de intensidades máximas y una variante de la misma en la cual se atenúa la intensidad de los objetos en función de la distancia de los mismos al observador. Se las implementó utilizando OpenGL vía texturas bidimensionales y texturas tridimensionales, se evaluaron cualitativamente la calidad de las representaciones, y se cuantificaron los tiempos de graficación. Finalmente, se analizaron las ventajas y desventajas del uso de las técnicas y de las herramientas disponibles para implementarlas en un programa.Sociedad Argentina de Informática e Investigación Operativ

Visualisierung zweidimensionaler Volumen

In dieser Arbeit wird ein neues Verfahren zur Visualisierung zweidimensionaler Volumen vorgestellt. Der Begriff multidimensionales Volumen wird dabei definiert als eine Menge von räumlich dreidimensionalen Datensätzen, die jeder eine andere Eigenschaft (eine physikalische Qualität, z.B. Dichte oder Temperatur) desselben Objekts beschreiben. Zweidimensionale Volumen beschreiben also zwei verschiedene Eigenschaften eines Objekts. Sie entstehen z.B. in biomedizinischen Anwendungen, wenn gleichzeitig funktionale und anatomische Datensätze untersucht werden. Zunächst wird der Stand der Technik in der Visualisierung zweidimensionaler Volumen dargelegt. Dabei sind besonders die folgenden Schwächen bestehender Verfahren erkennbar: - Schlechte räumliche Darstellung und schlechte Lokalisierbarkeit von Ausprägungen (bemerkenswerte Quantitäten einer Eigenschaft an einer Stelle). Beschränkung auf Datensätze aus speziellen Quellen oder spezielle Kombinationen von Datensätzen. - Prinzipbedingte Beschränkung einer Eigenschaft auf wenige kleine Regionen innerhalb der anderen Eigenschaft. Basierend auf diesen Defiziten werden die Anforderungen für ein besseres Visualisierungsverfahren herausgearbeitet, anhand derer ein neues Verfahren, dependent rendering genannt, entwickelt wird. Das Verfahren basiert auf der Annahme, dass bei der Visualisierung mehrerer Eigenschaften immer eine Eigenschaft als Referenz zur Lokalisierung dienen kann. Abhängig von der ersten kann eine weitere Eigenschaft visualisiert werden. Es werden drei Implementierungen des Verfahrens vorgestellt, die ersten beiden sind Prototypen, die dritte eine spezialisierte Anwendung für eine biomedizinische Visualisierungsplattform. Die Implementierungen veranschaulichen, dass sich das vorgestellte Verfahren gegenüber bestehenden Ansätzen besonders durch folgende Punkte auszeichnet: - Gute Lokalisierbarkeit von Ausprägungen bei gleichzeitiger guter räumlicher Darstellung des Objekts (z.B.: "Ist es auf der Oberfläche heiss oder innerhalb des Objekts?"). - Gleiche räumliche Ausdehnung beider Datensätze möglich. - Genereller Ansatz: Keine Beschränkung auf Datensätze aus speziellen Quellen oder auf spezielle Kombinationen von Datensätzen. Das vorgestellte Verfahren stellt daher einen bedeutenden Fortschritt in der Technik der Visualisierung zweier Eigenschaften eines Objekts dar.In this thesis, a new technique for the visualisation of two-dimensional volumes is presented. The term multi-dimensional volume is defined as a set of spatially three-dimensional data sets, each of them describing another property (a physical quality, e.g. density or temperature) of the same object. Thus, two-dimensional volumes describe two different properties of an object. They are used e.g. in biomedical imaging, where anatomical and functional data are examined jointly. First, the state of the art in the visualisation of two-dimensional volumes is presented. In the course of this, the following deficiencies of existing approaches become apparent: - Unsatisfactory 3D impression (it is difficult to mentally reconstruct the spatially three-dimensional object from the rendering) and difficult localisation of features (i.e. remarkable characteristics in the quantity of a property at a given location). - Restriction to data sets from particular origins or particular combinations of data sets. - By design, one property is restricted to only a few small regions inside the other property. Starting from these deficiencies, the requirements for a visualisation technique that overcomes these limitations are elaborated. These are then used to develop a new technique, called dependent rendering, which is based on the assumption that, when visualising two properties of an object, there is alway one property that can serve as a spatial reference for the other. The other property is then visualised in dependency on this reference. Three implementations of the technique are presented, the first two are prototypes, the third one is a specialised application for a biomedical visualisation platform. The implementations show that, compared to existing approaches, the presented technique especially stands out because of the following features: - Precise localisation of features combined with good 3D impression of the object (e.g. "Is it hot on the surface or only inside the object?"). - Both data sets can be extended over the same region. - General approach: No restriction to data sets from particular origins or particular combinations of data sets. The presented technique therefore represents an important advancement in the joint visualisation of two properties of an object

Visualisation volumique par projection du maximum d'intensité avec ondelettes

Les techniques d'acquisition en imagerie médicale génèrent de plus en plus de données. Les processus de visualisation demandent à être performants autant d'un point de vue vitesse de calcul que qualité de résultat. C'est pourquoi il est intéressant d'intégrer des outils de représentation de données efficaces comme les ondelettes, dans le but d'optimiser le stockage en mémoire, et les processus de traitement. Nous nous intéressons plus particulièrement à une méthode de visualisation très utilisée en imagerie médicale: la projection du maximum d'intensité (MIP); elle consiste à afficher uniquement la valeur maximale rencontrée sur chaque rayon de projection. Une nouvelle représentation des données volumiques est proposée s'inspirant de la théorie de l'ondelette morphologique et de l'algorithme proposé par Roerdink du MIP par représentation en pyramide d'adjonction. Deux approches de MIP progressif on été développées avec cette nouvelle représentation. La deuxième plus prometteuse permet une compression des données initiales de plus de 70% pour une qualité de résultats presque parfaite. Aussi, la vitesse d'exécution du MIP proposé rivalise avec celle des meilleurs algorithmes développés jusqu'à ce jour

Functional representation and manipulation of shapes with applications in surface and solid modeling

Real-valued functions have wide applications in various areas within computer graphics. In this work, we examine three representation of shapes using functions. In particular, we study the classical B-spline representation of piece-wise polynomials in the univariate domain. We provide a generalization of B-spline to the bivariate domain using intuition gained from the univariate construction. We also study the popular scheme of representing 3D density distribution using a uniform, rectilinear grid, where we provide a novel contouring scheme that culls occluded inner geometries. Lastly, we examine a ray-based representation for 3D indicator functions called ray-rep, for which we present a novel meshing scheme with multi-material extensions

Fast Visualization by Shear-Warp using Spline Models for Data Reconstruction

This work concerns oneself with the rendering of huge three-dimensional data sets. The target thereby is the development of fast algorithms by also applying recent and accurate volume reconstruction models to obtain at most artifact-free data visualizations. In part I a comprehensive overview on the state of the art in volume rendering is given. Part II is devoted to the recently developed trivariate (linear,) quadratic and cubic spline models defined on symmetric tetrahedral partitions directly obtained by slicing volumetric partitions of a three-dimensional domain. This spline models define piecewise polynomials of total degree (one,) two and three with respect to a tetrahedron, i.e. the local splines have the lowest possible total degree and are adequate for efficient and accurate volume visualization. The following part III depicts in a step by step manner a fast software-based rendering algorithm, called shear-warp. This algorithm is prominent for its ability to generate projections of volume data at real time. It attains the high rendering speed by using elaborate data structures and extensive pre-computation, but at the expense of data redundancy and visual quality of the finally obtained rendering results. However, to circumvent these disadvantages a further development is specified, where new techniques and sophisticated data structures allow combining the fast shear-warp with the accurate ray-casting approach. This strategy and the new data structures not only grant a unification of the benefits of both methods, they even easily admit for adjustments to trade-off between rendering speed and precision. With this further development also the 3-fold data redundancy known from the original shear-warp approach is removed, allowing the rendering of even larger three-dimensional data sets more quickly. Additionally, real trivariate data reconstruction models, as discussed in part II, are applied together with the new ideas to onward the precision of the new volume rendering method, which also lead to a one order of magnitude faster algorithm compared to traditional approaches using similar reconstruction models. In part IV, a hierarchy-based rendering method is developed which utilizes a wavelet decomposition of the volume data, an octree structure to represent the sparse data set, the splines from part II and a new shear-warp visualization algorithm similar to that presented in part III. This thesis is concluded by the results centralized in part V

Interactive High-Quality Maximum Intensity Projection

Maximum Intensity Projection (MIP) is a volume rendering technique which is used to visualize high-intensity structures within volumetric data. At each pixel the highest data value, which is encountered along a corresponding viewing ray is depicted. MIP is, for example, commonly used to extract vascular structures from medical data sets (angiography). Due to lack of depth information in MIP images, animation or interactive variation of viewing parameters is frequently used for investigation. Up to now no MIP algorithms exist which are of both interactive speed and high quality. In this paper we present a high-quality MIP algorithm (trilinear interpolation within cells), which is up to 50 times faster than brute-force MIP and at least 20 times faster than comparable optimized techniques. This speed-up is accomplished by using an alternative storage scheme for volume cells (sorted by value) and by removing cells which do not contribute to any MIP projection (regardless of the vie..