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Volume illustration can be used to provide insight into source data from CT/MRI scanners in much the same way as medical illustration depicts the important details of anatomical structures. As such, proven techniques used in medical illustration should be transferable to volume illustration, providing scientists with new tools to visualize their da...
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Context 1
... surface models, sometimes the "plane breaks," or fine- scale details, are contextually important. These details are sometimes represented by small bumps or cavities and are characterized by very little depth variance (Fig. 3a). Because of this, the original depth darkening approach fails to detect these ...
Context 2
... if we examine how the surface normals change for the same part of the volume, the magnitude of the change is much more substantial (Fig. 3b). Therefore, we have developed methods to analyze the normals' field and use it to highlight the needed surface ...
Context 3
... surface models, sometimes the "plane breaks," or fine- scale details, are contextually important. These details are sometimes represented by small bumps or cavities and are characterized by very little depth variance (Fig. 3a). Because of this, the original depth darkening approach fails to detect these ...
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... Volume Illustration [ER00] is a group of techniques that extend standard DVR by enabling the integration of non-photorealistic rendering techniques that modulate opacity and color of each sample based on local features in order to enhance certain structures. Svakhine et al. [SEA09] uses unsharp masking of the depth buffer to achieve an effect visually comparable to ambient occlusion, as it emphasizes cavities through the darkening effect. Bruckner et al. [BG07] integrate halo effects into GPU-based volume rendering to enhance and highlight structures of interest inside the volume, by mapping the halo intensity in color and opacity. ...
We propose a novel rendering framework for visualizing point data with complex structures and/or different quality of data.
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of the dataset (i.e. uncertainty given by local normal variation). Our rendering method uses the scalar field to render points
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... 1,2,[4][5][6][19][20][21] A few studies 15,22 reported the perceptual advantages of introducing motion parallax in the visualized transparent volumes. Advantages of simulated aerial perspective 14,15 (i.e., luminance contrast gradient in depth) and objects' edges 23 yielded by different visualization methods [24][25][26] have also been reported. ...
Transparent visualization is used in many fields because it can visualize not only the frontal object but also other important objects behind it. Although in many situations, it would be very important for the 3D structures of the visualized transparent images to be perceived as they are simulated, little is known quantitatively as to how such transparent 3D structures are perceived. To address this question, in the present study, we conducted a psychophysical experiment in which the observers reported the perceived depth magnitude of a transparent object in medical images, presented with a multi-view 3D display. For the visualization, we employed a stochastic point-based rendering (SPBR) method, which was developed recently as a technique for efficient transparent-rendering. Perceived depth of the transparent object was smaller than the simulated depth. We found, however, that such depth underestimation can be alleviated to some extent by (1) applying luminance gradient inherent in the SPBR method, (2) employing high opacities, and (3) introducing binocular disparity and motion parallax produced by a multi-view 3D display.
... These techniques, all consider depth values in the compositing equation, and have been selected based on initial perceptual findings, and the widespread usage in volume rendering, as determined based on exchange with other researchers and our own experience, as well as the number of citations of the publications proposing these techniques. Thus, we compare standard DVR to Depth of Field rendering [Schott et al. 2011], Depth Darkening [Svakhine et al. 2009], Volumetric Halos [ Bruckner and Gröller 2007], Volume Illustration [ Rheingans and Ebert 2001], and Volumetric Line Drawings [Burns et al. 2005]. An example for the application of each of these techniques is shown in Figure 1. ...
... By unsharp masking the depth buffer [Luft et al. 2006], Depth Darkening achieves an effect visually comparable to ambient occlusion, as it emphasizes cavities through the darkening effect. As it has also been applied in the area of volume rendering [Svakhine et al. 2009], we have chosen this approach for our evaluation. Volumetric Halos. ...
Direct volume rendering (DVR) provides the possibility to visualize volumetric data sets as they occur in many scientific disciplines. A key benefit of DVR is that semi-transparency can be facilitated in order to convey the complexity of the visualized data. Unfortunately, semi-transparency introduces new challenges in spatial comprehension of the visualized data, as the ambiguities inherent to semi-transparent representations affect spatial comprehension. Accordingly, many visualization techniques have been introduced to enhance the spatial comprehension of DVR images. In this paper, we conduct a user evaluation in which we compare standard DVR with five visualization techniques which have been proposed to enhance the spatial comprehension of DVR images. In our study, we investigate the perceptual performance of these techniques and compare them against each other to find out which technique is most suitable for different types of data and purposes. In order to do this, a large-scale user study was conducted with 300 participants who completed a number of micro-tasks designed such that the aggregated feedback gives us insight on how well these techniques aid the end user to perceive depth and shape of objects. Within this paper we discuss the tested techniques, present the conducted study and analyze the retrieved results.
... Chu et al. [CCG * 08] presented perception-aware depth cueing for illustrative vascular visualization, using depth-aware silhouettes, color-coded shading strokes and line-culling highlights. Svakhine et al. [SEA09] depth enhanced medical volume visualization with artistic styles for outlining features and conveying depth information. Hansen et al. [HWR * 10] visualized 3D planning models for augmented reality in liver surgery using illustrative techniques. ...
In medical visualization of surface information, problems often arise when visualizing several overlapping structures simultaneously. There is a trade-off between visualizing multiple structures in a detailed way and limiting visual clutter, in order to allow users to focus on the main structures. Illustrative visualization techniques can help alleviate these problems by defining a level of abstraction per structure. However, clinical uptake of these advanced visualization techniques so far has been limited due to the complex parameter settings required. To bring advanced medical visualization closer to clinical application, we propose a novel illustrative technique that offers a seamless transition between various levels of abstraction and detail. Using a single comprehensive parameter, users are able to quickly define a visual representation per structure that fits the visualization requirements for focus and context structures. This technique can be applied to any biomedical context in which multiple surfaces are routinely visualized, such as neurosurgery, radiotherapy planning or drug design. Additionally, we introduce a novel hatching technique, that runs in real-time and does not require texture coordinates. An informal evaluation with experts from different biomedical domains reveals that our technique allows users to design focus-and-context visualizations in a fast and intuitive manner.
... This is inspired by artists who use blue backgrounds to depict an aerial perspective. Svakhine et al. [SEA09] enhance depth perception for large-and small-scale features by employing color-based techniques which also mimic the effects of the aerial perspective. To give the user more control over how features are emphasized, Svakhine et al. introduce a depth filtering function, which allows depth enhancement to be constrained to a subset of the overall depth range. ...
This survey provides an overview of perceptually motivated techniques for the visualization of medical image data, including physics-based lighting techniques as well as illustrative rendering that incorporate spatial depth and shape cues. Additionally, we discuss evaluations that were conducted in order to study the perceptual effects of these visualization techniques as compared to conventional techniques. These evaluations assessed depth and shape perception with depth judgment, orientation matching, and related tasks. This overview of existing techniques and their evaluation serves as a basis for defining the evaluation process of medical visualizations and to discuss a research agenda.
... The first bone data was a CT hand (492 × 240 × 155), which was used by Svakhine et al. [36]. As shown in Fig. 3, unlike 3D video-fluoroscopy method [3,37], the proposed method need not to exploit segmentation procedure to reconstruct the 3D pose of objects. ...
Designing transfer functions is a challenging task for medical volume data visualization, especially when an arch of the same boundary disperses seriously and adjacent arches are intersected in the intensity and gradient magnitude (IGM) transfer function space. In this paper, a novel transfer function space is proposed to better highlight and differentiate different materials in realistic volume datasets. The proposed method combines the intensity values and three-dimensional (3D) SUSAN (Smallest Univalue Segment Assimilating Nucleus) edge responses of the original data to define the intensity and SUSAN (IS) transfer function space. The results of various datasets in volume rendering show that boundary of different materials exhibits a trapezoidal shape in the proposed IS space, and boundary information is much better brought out in comparison to the IGM space. Thus the IS space provides much more intuitive clues than the IGM space in order that transfer functions can be more easily designed. Meanwhile, more details of materials of interest are visible in the rendering images.
... Because of the versatility, Nielsen et al. (1994) asserted that volumetric visualization is very promising. Indeed this approach is wellapplied in medical research, in which human perception of depth and spatial relationships of objects is crucial (Svakhine, Ebert, & Andrews, 2009). However, the strength of showing all data is also a weakness, since it takes some training to be able to present and interpret such displays properly (Fortner, 1992). ...
... For example, if the data are from medical scanning devices, in which surgeons analyze them for surgical aids, precision is the prime criterion for a successful visualization. Under this circumstance all or most data must be included and a translucent volumetric model is probability most useful (Svakhine, Ebert, & Andrews, 2009). On the other hand, data for economic forecasts may need a smoother visualization technique, rather than a volumetric model, to indicate a trend. ...
The term “scientific visualization” was coined by a panel of the Association for Computing Machinery (ACM) organized by the National Sciences Foundation’s Division of Advanced Scientific Computing. At first the term “scientific visualization” was exclusively referred to as visualization in scientific and engineering computing, such computer modeling and simulation. Later visualization practices include data sources from other disciplines and eventually this movement merged with the movement of “information visualization,” which also started in the early 1990s. According to Few, “data visualization” is the umbrella term encompassing both scientific visualization and information visualization. It is important to point out that this book is not a manual of creating statistical graphs. Today software companies release new products or a new version of their products rapidly, and thus the best way to learn the interface is to visit their websites or view a tutorial on YouTube. Rather, the author intends to focus on the principles of data visualization, which tends to be stable for a while and can be well–applied across software modules. For a data analyst, what should be done and why so are more important than how it is done.
... Ⅳ. 변환 정보 추출 영상의 입체감을 개선하기 위해서 깊이맵으로부터 변환 정보(conversion information)를 획득한다. Ⅲ장에서 제안한 스테레오 매칭을 통해 깊이맵을 획득하였다면, 이 깊이맵 에 언샤프 마스킹(unsharp masking) 기술을 적용하여 변환 정보를 획득할 수 있다[16][17][18] . 본 논문에서는 깊이맵에 언샤 프 마스킹을 적용함으로써 깊이감을 개선하고자 하였다[16] . ...
Recently, 3DTV and 3D displays have been released in the market. Accordingly, the production of stereoscopic images has gained much interest. Stereoscopic image being composed of left and right images are currently delivered to viewers without any modifications. The researches on the enhancement of depth perception using high-frequency components and the re-production of natural color by color compensation have been carried out for 2D images. The application of such 2D technologies to 3D stereoscopic images is an aim of this paper. This paper proposes the enhancement of 3D perception by color transformation. For this, we propose a stereo matching method for obtaining a depth map and two color transformation methods such as contrast transformation and background darkening. The effectiveness of the proposed method was verified through experiments.
... The most detailed evaluations of how to improve a user's perception and spatial understanding of volumetric data focus on comparing different rendering techniques and/or different transfer functions [12,13,3,1]. A few authors have studied the effectiveness of stereoscopic display for volumetric data [6,5,9,8]. ...
Displays supporting stereopsis and head location based motion parallax can enhance human perception of complex three dimensional datasets. This has been demonstrated for datasets containing 3D surfaces and 3D networks. Yet many domains, such as medical imaging, weather and environment simulations and fluid flow, generate complex volumetric data. This poster present results of an initial formal experiment that examines the effectiveness of various display conditions on depth perception of volumetric data. There is an overall benefit for stereoscopy with head-tracking in enhancing depth perception. Further, familiarity with 3D games and VR-like hardware improves the users'ability to perceive such data.
... Furthermore, depth perception has been an important field of research in computer graphics. Especially for DVR many methods for enhancing depth cues have been proposed [1, 2, 4, 11, 12] . For translucent volumes (such as X-Ray) an existing method uses stere- oscopy [8]. ...
In this paper, we present an interactive X-Ray perceptual visualization technique (IXPV) to improve 3D perception in standard single-view X-Ray images. Based on a priori knowledge from CT data, we re-introduce lost depth information into the original single-view X-Ray image without jeopardizing information of the original X-Ray. We propose a novel approach that is suitable for correct fusion of intraoperative X-Ray and ultrasound, co-visualization of X-Ray and surgical tools, and for improving the 3D perception of standard radiographs. Phantom and animal cadaver datasets were used during experimentation to demonstrate the impact of our technique. Results from a questionnaire completed by 11 clinicians and computer scientists demonstrate the added value of introduced depth cues directly in an X-Ray image. In conclusion, we propose IXPV as a futuristic alternative to the standard radiographic image found in today's clinical setting.
