Interactive Volumetric Visual Analysis of Glycogen‐derived Energy Absorption in Nanometric Brain Structures

Digital acquisition and processing techniques are changing the way neuroscience investigation is carried out. Emerging applications range from statistical analysis on image stacks to complex connectomics visual analysis tools targeted to develop and test hypotheses of brain development and activity. In this work, we focus on neuroenergetics, a field where neuroscientists analyze nanoscale brain morphology and relate energy consumption to glucose storage in form of glycogen granules. In order to facilitate the understanding of neuroenergetic mechanisms, we propose a novel customized pipeline for the visual analysis of nanometric‐level reconstructions based on electron microscopy image data. Our framework supports analysis tasks by combining i) a scalable volume visualization architecture able to selectively render image stacks and corresponding labelled data, ii) a method for highlighting distance‐based energy absorption probabilities in form of glow maps, and iii) a hybrid connectivitybased and absorption‐based interactive layout representation able to support queries for selective analysis of areas of interest and potential activity within the segmented datasets. This working pipeline is currently used in a variety of studies in the neuroenergetics domain. Here, we discuss a test case in which the framework was successfully used by domain scientists for the analysis of aging effects on glycogen metabolism, extracting knowledge from a series of nanoscale brain stacks of rodents somatosensory cortex.     

基于GPU的三维医学图像混合可视化系统

研究并实现了一个基于GPU的医学图像混合可视化系统，该系统采用三维纹理映射的方法实现直接体绘制，利用GPU的可编程特性完成体绘制方法中的插值后分类算法和传输函数的传递及实时修改，采用OpenGL技术实现表面的绘制，并基于场景图结构实现时表面数据的管理。面绘制和体绘制部分都采用OpenGL实现，运用OpenGL的融合机制，系统实现了面绘制和体绘制的混合显示。本系统大大提高了体绘制的速度，有效地保留了面绘制和体绘制的优势，在保证绘制速度的基础上丰富了图像信息。     

基于MATLAB GUI图像处理系统的设计与实现

MATLAB作为算法开发及数据可视化的交互式工具,在数字图像处理方面应用广泛,并集成了具有多种算法的图像处理工具箱。本文基于MATLAB图像用户界面(GUI)和图像处理工具箱设计实现了一款图像处理系统,该系统可实现图像的运算、变换、分割、改善、形态学处理、压缩编码等内容,并通过综合实例阐述了本系统在图像识别中的应用,使图像处理可视化更加直观,便捷。多次实践表明,本系统具有良好的实用性、交互性、移植性,易于后期模式识别和机器视觉相关应用的扩展研究。     

RETRACTED ARTICLE: Texture-guided volumetric deformation and visualization using 3D moving least squares

Examining and manipulating the large volumetric data attract great interest for various applications. For such purpose, we first extend the 2D moving least squares (MLS) technique into 3D, and propose a texture-guided deformation technique for creating visualization styles through interactive manipulations of volumetric models using 3D MLS. Our framework includes focus+context (F+C) visualization for simultaneously showing the entire model after magnification, and the cut-away or illustrative visualization for providing a better understanding of anatomical and biological structures. Both visualization styles are widely applied in the graphics areas. We present a mechanism for defining features using high-dimensional texture information, and design an interface for visualizing, selecting and extracting features/objects of interest. Methods of the interactive or automatic generation of 3D control points are proposed for the flexible and plausible deformation. We describe a GPU-based implementation to achieve real-time performance of the deformation techniques and the manipulation operators. Different from physical deformation models, our framework is goal-oriented and user-guided. We demonstrate the robustness and efficiency of our framework using various volumetric datasets.     

Noise- and compression-robust biological features for texture classification

Texture classification is an important aspect of many digital image processing applications such as surface inspection, content-based image retrieval, and biomedical image analysis. However, noise and compression artifacts in images cause problems for most texture analysis methods. This paper proposes the use of features based on the human visual system for texture classification using a semisupervised, hierarchical approach. The texture feature consists of responses of cells which are found in the visual cortex of higher primates. Classification experiments on different texture libraries indicate that the proposed features obtain a very high classification near 97%. In contrast to other well-established texture analysis methods, the experiments indicate that the proposed features are more robust to various levels of speckle and Gaussian noise. Furthermore, we show that the classification rate of the textures using the presented biologically inspired features is hardly affected by image compression techniques.     

岩石材料变形破坏过程应用程序开发

为了研究岩石表面变形破坏过程的变化特征,设计了一个可视化应用程序.该应用程序以岩石常规力学性质试验视频作为研究对象,包括静态图像处理界面和视频图像处理界面.静态图像处理界面由图像类型转换、图像边缘检测、图像形态学处理、图像滤波处理4个模块组成.视频处理界面则提供试验视频帧数、历时、帧图像大小和维数等基本信息.通过在可视化界面上进行所需参数设置实现了单帧图像特征纹理参数计算和岩石试样表面位移场的计算.本文还以两个示例说明了使用该应用程序进行岩石材料变形破坏过程分析的方法.本文成果对分析岩石材料变形特点和破坏机制具有一定的参考价值.     

Task-based annotation and retrieval for image information management

Continuing advances in digital image capture and storage are resulting in a proliferation of imagery and associated problems of information overload in image domains. In this work we present a framework that supports image management using an interactive approach that captures and reuses task-based contextual information. Our framework models the relationship between images and domain tasks they support by monitoring the interactive manipulation and annotation of task-relevant imagery. During image analysis, interactions are captured and a task context is dynamically constructed so that human expertise, proficiency and knowledge can be leveraged to support other users in carrying out similar domain tasks using case-based reasoning techniques. In this article we present our framework for capturing task context and describe how we have implemented the framework as two image retrieval applications in the geo-spatial and medical domains. We present an evaluation that tests the efficiency of our algorithms for retrieving image context information and the effectiveness of the framework for carrying out goal-directed image tasks.     

Visualizing multiwavelength astrophysical data

With recent advances in the measurement technology for allsky astrophysical imaging, our view of the sky is no longer limited to the tiny visible spectral range over the 2D Celestial sphere. We now can access a third dimension corresponding to a broad electromagnetic spectrum with a wide range of allsky surveys; these surveys span frequency bands including long wavelength radio, microwaves, very short X-rays, and gamma rays. These advances motivate us to study and examine multiwavelength visualization techniques to maximize our capabilities to visualize and exploit these informative image data sets. In this work, we begin with the processing of the data themselves, uniformizing the representations and units of raw data obtained from varied detector sources. Then we apply tools to map, convert, color-code, and format the multiwavelength data in forms useful for applications. We explore different visual representations for displaying the data, including such methods as textured image stacks, the horseshoe representation, and GPU-based volume visualization. A family of visual tools and analysis methods is introduced to explore the data, including interactive data mapping on the graphics processing unit (GPU), the mini-map explorer, and GPU-based interactive feature analysis.     

Flow charts: visualization of vector fields on arbitrary surfaces

We introduce a novel flow visualization method called Flow Charts, which uses a texture atlas approach for the visualization of flows defined over curved surfaces. In this scheme the surface and its associated flow are segmented into overlapping patches which are then parameterized and packed in the texture domain. This scheme allows accurate particle advection across multiple charts in the texture domain, providing a flexible framework that supports various flow visualization techniques. The use of surface parameterization enables flow visualization techniques requiring the global view of the surface over long time spans, such as Unsteady Flow LIC (UFLIC), particle-based Unsteady Flow Advection-Convolution (UFAC), or dye advection. It also prevents visual artifacts normally associated with view-dependent methods. Represented as textures, Flow Charts can be naturally integrated into GPU flow visualization techniques for interactive performance.     

Wavelet-Based 3D Compression Scheme for Interactive Visualization of Very Large Volume Data

Interactive visualization of very large volume data has been recognized as a task requiring great effort in a variety of science and engineering fields. In particular, such data usually places considerable demands on run-time memory space. In this paper, we present an effective 3D compression scheme for interactive visualization of very large volume data, that exploits the power of wavelet theory. In designing our method, we have compromised between two important factors: high compression ratio and fast run-time random access ability. Our experimental results on the Visual Human data sets show that our method achieves fairly good compression ratios. In addition, it minimizes the overhead caused during run-time reconstruction of voxel values. This 3D compression scheme will be useful in developing many interactive visualization systems for huge volume data, especially when they are based on personal computers or workstations with limited memory.     

Visualization of fibrous and thread-like data

Thread-like structures are becoming more common in modern volumetric data sets as our ability to image vascular and neural tissue at higher resolutions improves. The thread-like structures of neurons and micro-vessels pose a unique problem in visualization since they tend to be densely packed in small volumes of tissue. This makes it difficult for an observer to interpret useful patterns from the data or trace individual fibers. In this paper we describe several methods for dealing with large amounts of thread-like data, such as data sets collected using Knife-Edge Scanning Microscopy (KESM) and Serial Block-Face Scanning Electron Microscopy (SBF-SEM). These methods allow us to collect volumetric data from embedded samples of whole-brain tissue. The neuronal and microvascular data that we acquire consists of thin, branching structures extending over very large regions. Traditional visualization schemes are not sufficient to make sense of the large, dense, complex structures encountered. In this paper, we address three methods to allow a user to explore a fiber network effectively. We describe interactive techniques for rendering large sets of neurons using self-orienting surfaces implemented on the GPU. We also present techniques for rendering fiber networks in a way that provides useful information about flow and orientation. Third, a global illumination framework is used to create high-quality visualizations that emphasize the underlying fiber structure. Implementation details, performance, and advantages and disadvantages of each approach are discussed.     

Visualization of Large‐Scale Urban Models through Multi‐Level Relief Impostors

In this paper, we present an efficient approach for the interactive rendering of large‐scale urban models, which can be integrated seamlessly with virtual globe applications. Our scheme fills the gap between standard approaches for distant views of digital terrains and the polygonal models required for close‐up views. Our work is oriented towards city models with real photographic textures of the building facades. At the heart of our approach is a multi‐resolution tree of the scene defining multi‐level relief impostors. Key ingredients of our approach include the pre‐computation of a small set of zenithal and oblique relief maps that capture the geometry and appearance of the buildings inside each node, a rendering algorithm combining relief mapping with projective texture mapping which uses only a small subset of the pre‐computed relief maps, and the use of wavelet compression to simulate two additional levels of the tree. Our scheme runs considerably faster than polygonal‐based approaches while producing images with higher quality than competing relief‐mapping techniques. We show both analytically and empirically that multi‐level relief impostors are suitable for interactive navigation through large urban models.     

Scalable 3-D Terrain Visualization Through Reversible JPEG2000-Based Blind Data Hiding

In this paper a new method is presented for 3-D terrain visualization via reversible JPEG2000-based blind data hiding with special focus on data synchronization and scalability. Online real-time 3-D terrain visualization involves considerable amount of data. The process is essentially the mapping of the aerial photograph, called texture, onto its corresponding digital elevation model (DEM) implying at least two distinct data inputs. The presence of large disparate data necessitates a compression strategy on one hand and the integration of the DEM and texture into one unit on the other. Whilst the compression must accommodate the scalability requirement originated by the diversity of clients, the unification of data ought to be synchronous. For scalability this paper relies on the multiresolution nature of the DWT-based JPEG2000 standard whereas the synchronized unification of DEM with the texture is realized by the application of a perceptually transparent data hiding strategy in the DWT domain. The proposed method is blind in the sense that only a secret key, if any, and the size of the original DEM are needed to extract the data from the texture image. We believe that this is one of the pioneering methods to propose scalable embedding of DEM in the texture image. The method is cost effective, in terms of memory and bandwidths, which is an advantage, especially, in real-time environments when quicker transfer of data is required. The results of a 3-D visualization simulation effected with our method were encouraging and gave a useful insight to the effectiveness of our method in various bandwidth scenarios.      

统一的数字几何处理框架

随着三维几何模型在工业界的广泛应用，处理几信号的算法变得越来越重要。尽管近几年数字几何处理研究有了很大的进展，仍然缺乏一个类似于数字图像处理的统一解决方案。该文提出了任意网格的数字信号处理框架，很好地满足了这一需求。该框架的核心思想是通过为任意网格模型构造一个全局球面（或平面）参数化，把模型的所有属性转化为定义在球面（或平面）上的信号，然后采用球面（或平面）正交分析工具对这些信号做分析处理。在这两个框架下，所有的数字图像处理技术都可以被扩展到网格模型。该文还给出了包括滤波、多分辨率编辑和压缩在内的几种典型应用的实现方法和试验结果。     

数字半调技术及其评价方法研究

数字半色调技术是在二值设备或有限灰度级设备上实现图像再现的一门技术,广泛应用于印刷打印、压缩等领域。针对这一基础性图像处理技术——图像处理支撑技术数字半调技术进行了综述,分析了数字半调技术的现状,对经典算法和最新进展进行了介绍。并通过多种评价方法对半调算法进行了量化比较和分析,展望了数字半色调技术的发展趋势。     

Real-time virtual environment signal extraction and denoising using programmable graphics hardware

The sense of being within a three-dimensional (3D) space and interacting with virtual 3D objects in a computer-generated virtual environment (VE) often requires essential image, vision and sensor signal processing techniques such as differentiating and denoising. This paper describes novel implementations of the Gaussian filtering for characteristic signal extraction and wavelet-based image denoising algorithms that run on the graphics processing unit (GPU). While significant acceleration over standard CPU implementations is obtained through exploiting data parallelism provided by the modern programmable graphics hardware, the CPU can be freed up to run other computations more efficiently such as artificial intelligence (AI) and physics. The proposed GPU-based Gaussian filtering can extract surface information from a real object and provide its material features for rendering and illumination. The wavelet-based signal denoising for large size digital images realized in this project provided better realism for VE visualization without sacrificing real-time and interactive performances of an application.     

交互式虚拟内窥镜系统

计算机图形图象技术与虚拟现实技术应用于医学内窥镜系统,产生了虚拟内窥镜技术,为了将虚拟现实技术应用在医学图象处理方面,以方便医生进行虚拟手术与无创诊断,在综合利用各种计算机图形,图象技术的基础上,提出了完整的交互式虚拟内窥镜系统的框架,同时对系统结构和各种模型进行了分析和讨论,还针对系统的实时性和绘制结果的逼真性要求,提出了基于Object Cache和扩展的区域增长方法,并将其应用到医学图象处理当中,得到了较好的效果,该系统较好地解决了虚拟现实与可视化实时性和绘制精度两方面的要求,从而为医学图象可视化提供了有力的工具。     

Interactive visualization of three-dimensional vector fields with flexible appearance control

In this paper, we present an interactive texture-based algorithm for visualizing three-dimensional steady and unsteady vector fields. The goal of the algorithm is to provide a general volume rendering framework allowing the user to compute three-dimensional flow textures interactively and to modify the appearance of the visualization on the fly. To achieve our goal, we decouple the visualization pipeline into two disjoint stages. First, flow lines are generated from the 3D vector data. Various geometric properties of the flow paths are extracted and converted into a volumetric form using a hardware-assisted slice sweeping algorithm. In the second phase of the algorithm, the attributes stored in the volume are used as texture coordinates to look up an appearance texture to generate both informative and aesthetic representations of the vector field. Our algorithm allows the user to interactively navigate through different regions of interest in the underlying field and experiment with various appearance textures. With our algorithm, visualizations with enhanced structural perception using various visual cues can be rendered in real time. A myriad of existing geometry-based and texture-based visualization techniques can also be emulated.