Visibility histograms and visibility-driven transfer functions

Direct volume rendering is an important tool for visualizing complex data sets. However, in the process of generating 2D images from 3D data, information is lost in the form of attenuation and occlusion. The lack of a feedback mechanism to quantify the loss of information in the rendering process makes the design of good transfer functions a difficult and time consuming task. In this paper, we present the general notion of visibility histograms, which are multidimensional graphical representations of the distribution of visibility in a volume-rendered image. In this paper, we explore the 1D and 2D transfer functions that result from intensity values and gradient magnitude. With the help of these histograms, users can manage a complex set of transfer function parameters that maximize the visibility of the intervals of interest and provide high quality images of volume data. We present a semiautomated method for generating transfer functions, which progressively explores the transfer function space toward the goal of maximizing visibility of important structures. Our methodology can be easily deployed in most visualization systems and can be used together with traditional 1D and 2D opacity transfer functions based on scalar values, as well as with other more sophisticated rendering algorithms.     

Illustrating volume data sets and layered models with importance-aware composition

Non-photorealistic (illustrative) rendering augments typical rendering models to selectively emphasize or de-emphasize specific structures of rendered objects. Illustrative techniques may affect not only the rendering style of specific portions of an object but also their visibility, ensuring that less important regions do not occlude more important ones. Cutaway views completely remove occluding, unimportant structures—possibly also removing valuable context information—while existing solutions for smooth reduction of occlusion based on importance lack precise visibility control, simplicity and generality. We introduce a new front-to-back fragment composition equation that directly takes into account a measure of sample importance and allows smooth and precise importance-based visibility control. We demonstrate the generality of our composition equation with several illustrative effects, which were obtained by using a set of importance measures calculated on the fly or defined by the user. The presented composition method is suitable for direct volume rendering as well as rendering of layered 3D models. We discuss both cases and show examples, though focusing mainly on illustration of volumetric data.     

基于有效裁剪被遮挡单元的非规则数据场体绘制算法

提出了一种被遮挡单元的裁剪算法,以加速非规则数据场的体绘制过程。在基于一组平行切割平面的体绘制方法上,新算法通过对图像不透明度缓冲区中的值进行求平均操作,并将所计算的结果存储在一个与不透明度缓冲区间同样大小的平均不透明度缓冲区中,使得只需根据每一数据单元重心投影点在平均不透明度缓冲区中的值,就可得到此数据单元的可见性,从而有效裁剪掉被遮挡单元,降低需处理的数据量,加速体绘制过程。     

基于结构特征的自适应光线投射算法

目的 光线投射法是一种重要的直接体绘制算法,但其效果取决于复杂的传递函数.为此提出基于结构特征的自适应光线投射算法,从而使得利用简单传递函数即可很好地揭示体数据特征.方法 首先分析光线方向标量值的变化趋势获取结构特征——特征段;然后基于若干意义明确启发式规则(特征段的次序、尺度、重要度)自动计算特征段的可见度,根据特征段可见度调节每个采样点的不透明度;最后基于调节后的不透明度完成绘制.结果 使用合成数据、医学真实采样数据和工业CT(computed tomography)数据进行测试,结果表明本文算法在展示体数据的内部结构特征,尤其是细小结构方面优于其他类似算法;本文算法速度比DVR(direct volume rendering)慢,但仍可满足交互需求.另外,本文算法还提供多个形象直观、意义明确的参数供用户调节,进一步增加了本文算法的灵活性.结论 本文提出的自适应光线投射算法,允许用户使用简单传递函数和调节意义明显的参数即可有效揭示体数据特征,进一步提高了光线透射法的直观性.     

Prostate Cancer Visualization from MR Imagery and MR Spectroscopy

Prostate cancer is one of the most prevalent cancers among males, and the use of magnetic resonance imaging (MRI) has been suggested for its detection. A framework is presented for scoring and visualizing various MR data in an efficient and intuitive manner. A classification method is introduced where a cumulative score volume is created which takes into account each of three acquisition types. This score volume is integrated into a volume rendering framework which allows the user to view the prostate gland, the multi‐modal score values, and the surrounding anatomy. A visibility persistence mode is introduced to automatically avoid full occlusion of a selected score and indicate overlaps. The use of GPU‐accelerated multi‐modal single‐pass ray casting provides an interactive experience. User driven importance rendering allows the user to gain insight into the data and can assist in localization of the disease and treatment planning. We evaluate our results against pathology and radiologists'determinations.     

应用于传递函数设定的交互式体绘制工具

传递函数是体绘制过程中用以定出体数据与光学特征的对应关系,因此,传递函数的设定对成像质量有着直接的影响,文章提出一应用于传递函数设定、简单且有效的交互式体绘制工具,由于二维纹理硬件在通用的个人计算机上被普遍使用,因而该工具采用基于二维纹理硬件的体绘制方法,利用本工具,用户能根据体数据的直方图来交互地分别设定R、G、B和A四种传递函数,以定出体数据与光学特征的对应关系,并获得实时的反馈视觉信息(绘制结果),该工具亦提供一虚拟轨迹球让用户交互地改变观察体数据的视点,用户不但可以交互地控制放大或缩小比率来绘制体数据,还可以选择采用光照或由多重纹理实现的三线性插值来获得不同的绘制效果,该文描述开发此工具的各种技术,并给出利用此工具得到的一些绘制结果。     

Volume seeds: A volume exploration technique

Ray-traced volume rendering has been shown to be an effective method for visualizing 3D scalar data. However, with currently available workstation technology, interactive volume exploration using conventional volume rendering is still too slow to be attractive. This paper describes an enhanced volume rendering method which allows interactive changes of rendering parameters such as colour and opacity maps. An innovative technique is provided which allows the user to plant a ‘seed’ in the volume to rapidly modify local shading parameters. For a fixed viewing position, the user can interactively explore specific regions of interest. Furthermore, a virtual cutting technique with the exploratory seed allows the user to remove surfaces and see the internal structure of the volume. Examples demonstrate these techniques as an attractive option in many applications.     

Rule‐Enhanced Transfer Function Generation for Medical Volume Visualization

In volume visualization, transfer functions are used to classify the volumetric data and assign optical properties to the voxels. In general, transfer functions are generated in a transfer function space, which is the feature space constructed by data values and properties derived from the data. If volumetric objects have the same or overlapping data values, it would be difficult to separate them in the transfer function space. In this paper, we present a rule‐enhanced transfer function design method that allows important structures of the volume to be more effectively separated and highlighted. We define a set of rules based on the local frequency distribution of volume attributes. A rule‐selection method based on a genetic algorithm is proposed to learn the set of rules that can distinguish the user‐specified target tissue from other tissues. In the rendering stage, voxels satisfying these rules are rendered with higher opacities in order to highlight the target tissue. The proposed method was tested on various volumetric datasets to enhance the visualization of important structures that are difficult to be visualized by traditional transfer function design methods. The results demonstrate the effectiveness of the proposed method.     

On Enhancing the Speed of Splatting Using Both Object- and Image-Space Coherence

Splatting is an object-order volume rendering algorithm that produces images of high quality, and for which several optimization techniques have been proposed. This paper presents new techniques that accelerate splatting algorithms by exploiting both object-space and image-space coherence. In particular, we propose two visibility test methods suitable for octree-based splatting. The first method, based on dynamic image-space range trees, offers an accurate occlusion test and does not trade off image quality. The second method, based on image-space quadtrees, uses an approximate occlusion test that is faster than the first algorithm. Although the approximate visibility test may produce visual artifacts in rendering, the introduced error is usually not found very often. Tests with several datasets of useful sizes and complexities showed considerable speedups with respect to the splatting algorithm enhanced with octree only. Considering that they are very easy to implement, and need little additional memory, our techniques will be used as very effective splatting methods.     

Shear–rotation–warp volume rendering

Shear–warp volume rendering has the advantages of a moderate image quality and a fast rendering speed. However, in the case of dynamic changes in the opacity transfer function, the efficiency of memory access drops, as the method cannot exploit pre‐classified volumes. In this paper, we propose an efficient algorithm that exploits the spatial locality of memory references for interactive classifications. The algorithm inserts a rotation matrix when factorizing the viewing transformation, so that it may perform a scanline‐based traversal in both object space and image space. In addition, we present solutions to some problems of the proposed method, namely inaccurate front‐to‐back composition, the occurrence of holes, and increased computation. Our method is noticeably faster than traditional shear‐warp rendering methods because of an improved utilization of cache memory. Copyright © 2005 John Wiley & Sons, Ltd.     

Fast Volume Rendering and Data Classification Using Multiresolution in Min‐Max Octrees

Large‐sized volume datasets have recently become commonplace and users are now demanding that volume‐rendering techniques to visualise such data provide acceptable results on relatively modest computing platforms. The widespread use of the Internet for the transmission and/or rendering of volume data is also exerting increasing demands on software providers. Multiresolution can address these issues in an elegant way. One of the fastest volume‐rendering alrogithms is that proposed by Lacroute & Levoy ¹ , which is based on shear‐warp factorisation and min‐max octrees (MMOs). Unfortunately, since an MMO captures only a single resolution of a volume dataset, this method is unsuitable for rendering datasets in a multiresolution form. This paper adapts the above algorithm to multiresolution volume rendering to enable near‐real‐time interaction to take place on a standard PC. It also permits the user to modify classification functions and/or resolution during rendering with no significant loss of rendering speed. A newly‐developed data structure based on the MMO is employed, the multiresolution min‐max octree, M ³ O, which captures the spatial coherence for datasets at all resolutions. Speed is enhanced by the use of multiresolution opacity transfer functions for rapidly determining and discarding transparent dataset regions. Some experimental results on sample volume datasets are presented.     

A language for the classification and shading of multivariate volume data

A novel, language-based interface to the specification of multivariate volume classification and shading algorithms has been implemented. The system facilitates experimentation by providing access to data relevant to volume classification and shading (scalars, gradients, and gradient magnitudes) in a C-like language environment. The user writes code to calculate opacity and colour on a per voxel basis. The code is interpreted and compiled in a transparent fashion and then executed on a volume data-set. The output is a volume primitive suitable for input to standard volume rendering algorithms.     

Integrating Occlusion Culling and Levels of Detail through Hardly-Visible Sets

Occlusion culling and level-of-detail rendering have become two powerful tools for accelerating the handling of very large models in real-time visualization applications. We present a framework that combines both techniques to improve rendering times. Classical occlusion culling algorithms compute potentially visible sets (PVS), which are supersets of the sets of visible polygons. The novelty of our approach is to estimate the degree of visibility of each object of the PVS using synthesized coarse occluders. This allows to arrange the objects of each PVS into several Hardly-Visible Sets (HVS) with similar occlusion degree. According to image accuracy and frame rate requirements, HVS provide a way to avoid sending to the graphics pipeline those objects whose pixel contribution is low due to partial occlusion. The image error can be bounded by the user at navigation time. On the other hand, as HVS offer a tighter estimation of the pixel contribution for each scene object, it can be used for a more convenient selection of the level-of-detail at which objects are rendered. In this paper, we describe the new framework technique, provide details of its implementation using a visibility octree as the chosen occlusion culling data structure and show some experimental results on the image quality.     

A Multidirectional Occlusion Shading Model for Direct Volume Rendering

In this paper, we present a novel technique which simulates directional light scattering for more realistic interactive visualization of volume data. Our method extends the recent directional occlusion shading model by enabling light source positioning with practically no performance penalty. Light transport is approximated using a tilted cone‐shaped function which leaves elliptic footprints in the opacity buffer during slice‐based volume rendering. We perform an incremental blurring operation on the opacity buffer for each slice in front‐to‐back order. This buffer is then used to define the degree of occlusion for the subsequent slice. Our method is capable of generating high‐quality soft shadowing effects, allows interactive modification of all illumination and rendering parameters, and requires no pre‐computation.     

Local histograms for design of transfer functions in direct volume rendering

Direct volume rendering (DVR) is of increasing diagnostic value in the analysis of data sets captured using the latest medical imaging modalities. The deployment of DVR in everyday clinical work, however, has so far been limited. One contributing factor is that current transfer function (TF) models can encode only a small fraction of the user's domain knowledge. In this paper, we use histograms of local neighborhoods to capture tissue characteristics. This allows domain knowledge on spatial relations in the data set to be integrated into the TF. As a first example, we introduce partial range histograms in an automatic tissue detection scheme and present its effectiveness in a clinical evaluation. We then use local histogram analysis to perform a classification where the tissue-type certainty is treated as a second TF dimension. The result is an enhanced rendering where tissues with overlapping intensity ranges can be discerned without requiring the user to explicitly define a complex, multidimensional TF     

Texture-based volume rendering of adaptive mesh refinement data

Many phenomena in nature and engineering happen simultaneously on rather diverse spatial and temporal scales. In other words, they exhibit a multi-scale character. A special numerical multilevel technique associated with a particular hierarchical data structure is adaptive mesh refinement (AMR). This scheme achieves locally very high spatial and temporal resolutions. Due to its popularity, many scientists are in need of interactive visualization tools for AMR data. In this article, we present a 3D texture-based volume-rendering algorithm for AMR data that directly utilizes the hierarchical structure. Thereby fast rendering performance is achieved even for high-resolution data sets. To avoid multiple rendering of regions that are covered by grids of different levels of resolution, we propose a space partitioning scheme to decompose the volume into axis-aligned regions of equal-sized cells. Furthermore the problems of interpolation artifacts, opacity corrections, and texture memory limitations are addressed. Published online: November 6, 2002 Correspondence to: R. K?hler     

一种基于交互式多维传递函数的纹理映射体绘制算法

本文设计了一种基于空间信息的交互式多维传递函数的纹理映射体绘制算法。该算法不仅可以根据体数据的强度而且还利用体素的空间位置来设定绘制的颜色和阻光度。通过采用一种独特的空间投影变换,根据用户需求,将体数据划分为不同区域,并分别定义各自的传递函数。该特点使得本文的算法可以有效地对体数据进行交互式分析。在算法实现中,利用了通用图形硬件的可编程特性,在普通PC上可以达到理想的绘制质量和交互速度。     

Incremental Volume Rendering Using Hierarchical Compression

We present a new algorithm here for efficient incremental rendering of volumetric datasets. The primary goal of this algorithm is to give average workstations the ability to efficiently render volume data received over relatively low bandwidth network links in such a way that rapid user feedback is maintained. Common limitations of workstation rendering of volume data include: large memory overheads, the requirement of expensive rendering hardware, and high speed processing ability. The rendering algorithm presented here overcomes these problems by making use of the efficient Shear-Warp Factorisation method which does not require specialised graphics hardware. However the original Shear-Warp algorithm suffers from a high memory overhead and does not provide for incremental rendering which is required should rapid user feedback be maintained. Our algorithm represents the volumetric data using a hierarchical data structure which provides for the incremental classification and rendering of volume data. This exploits the multiscale nature of the octree data structure. The algorithm reduces the memory footprint of the original Shear-Warp Factorisation algorithm by a factor of more than two, while maintaining good rendering performance. These factors make our octree algorithm more suitable for implementation on average desktop workstations for the purposes of interactive exploration of volume models over a network. Results from tests using typical volume datasets will be presented which demonstrate the ability of the algorithm to achieve high rendering rates for both incremental rendering and standard rendering while reducing the runtime memory requirements.     

An efficient GPU out‐of‐core framework for interactive rendering of large‐scale CAD models

Real‐time rendering of large‐scale engineering computer‐aided design (CAD) models has been recognized as a challenging task. Because of the constraints of limited graphics processing unit (GPU) memory size and computation capacity, a massive model with hundreds of millions of triangles cannot be loaded and rendered in real‐time using most of modern GPUs. In this paper, an efficient GPU out‐of‐core framework is proposed for interactively visualizing large‐scale CAD models. To improve efficiency of data fetching from CPU host memory to GPU device memory, a parallel offline geometry compression scheme is introduced to minimize the storage cost of each primitive by compressing the levels of detail (LOD) geometries into a highly compact format. At the rendering stage, occlusion culling and LOD processing algorithms are integrated and implemented with an efficient GPU‐based approach to determine a minimal scale of primitives to be transferred for each frame. A prototype software system is developed to preprocess and render massive CAD models with the proposed framework. Experimental results show that users can walkthrough massive CAD models with hundreds of millions of triangles at high frame rates using our framework. Copyright © 2016 John Wiley & Sons, Ltd.     

Scalable hybrid unstructured and structured grid raycasting

This paper presents a scalable framework for real-time raycasting of large unstructured volumes that employs a hybrid bricking approach. It adaptively combines original unstructured bricks in important (focus) regions, with structured bricks that are resampled on demand in less important (context) regions. The basis of this focus+context approach is interactive specification of a scalar degree of interest (DOI) function. Thus, rendering always considers two volumes simultaneously: a scalar data volume, and the current DOI volume. The crucial problem of visibility sorting is solved by raycasting individual bricks and compositing in visibility order from front to back. In order to minimize visual errors at the grid boundary, it is always rendered accurately, even for resampled bricks. A variety of different rendering modes can be combined, including contour enhancement. A very important property of our approach is that it supports a variety of cell types natively, i.e., it is not constrained to tetrahedral grids, even when interpolation within cells is used. Moreover, our framework can handle multi-variate data, e.g., multiple scalar channels such as temperature or pressure, as well as time-dependent data. The combination of unstructured and structured bricks with different quality characteristics such as the type of interpolation or resampling resolution in conjunction with custom texture memory management yields a very scalable system.