Fourier volume rendering

Malzbender, Tom

doi:10.1145/169711.169705

Cited by 178 publications

(88 citation statements)

References 9 publications

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“…The classic direct volume rendering method is the imagespace oriented ray casting algorithm. Moreover, some algorithms use domain-base techniques -the spatial volume data is first transformed into an alternative domain, such as frequency or wavelet, and then a projection is generated directly from this domain (Malzbender, 1993). Modern graphics cards are characterized by immense ability of 3D data processing.…”

Section: Visualisationmentioning

confidence: 99%

Virtual Colonoscopy - Technical Aspects

Skalski¹,

Socha²,

Zieliński³

et al. 2011

Colonoscopy

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Section: Visualisationmentioning

confidence: 99%

Virtual Colonoscopy - Technical Aspects

Skalski¹,

Socha²,

Zieliński³

et al. 2011

Colonoscopy

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“…Designing this method, we were inspired by both Fourier projection slicing volume rendering, such as in [13] or [19] and by splatting methods [9]. It is founded on the observation, that for many applications, as in medical imaging, X-ray like images are even superior for interactive data exploration and analysis.…”

Section: Wavelet Splatsmentioning

confidence: 99%

“…Recent approaches also include hybrid rendering methods [8], which link both paradigms. Other fundamental techniques are given with various types of transform domain volume rendering, where Fourier spaces have been explored succesfully [13], [19]. Unfortunately, beside of some computational advantages especially Fourier based methods are prone to major shortcomings regarding sampling, progressivity, filtering, local level of detail or transfer functions.…”

Section: Introductionmentioning

confidence: 99%

Two methods for wavelet-based volume rendering

Groß

Lippert

Dittrich

et al. 1997

Computers & Graphics

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-This paper describes two methods for wavelet domain rendering of volume data sets, which base on entire different paradigms for the approximation of the underlying volume rendering equation. The first approach comprises a ray-tracing algorithm for cardinal B-spline wavelet representations of both color and opacity values and carries out high quality images. We especially propose elaborated integration and evaluation schemes, where the computation of shading is also performed in wavelet space. The second approach proposes a fast intensity integration method based on wavelet splats. This scheme takes advantage from the self-similarity of the basis functions and computes the required splats by Fourier projection slicing. At this point, it unifies the advantages coming along with Fourier domain and with wavelet domain rendering and it avoids some of the major artifacts the first one is prone to. Due to the computational efficiency, the splatting method allows to compute coarse approximations at interactive rates and refines the picture progressively.

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“…Introduced by Levoy [8] and Malzbender [9], this method sacrifices some features -which object space algorithms offer-against rendering speed. In FVR, the original dataset is 3D Fourier transformed in O(N 3 logN ) time in the preprocessing phase.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Fourier Volume Rendering Using Contour Extraction

Nagy

Novotni

Klein

2004

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004

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Abstract. Fourier Volume Rendering (FVR) has received considerable attention in volume visualization during the last decade due its O(N 2 logN ) rendering time complexity, where O(N 3 ) is the volume size. Nevertheless, FVR currently suffers from some quality limiting its usefulness in particular medical applications. The main reason for this is the lack of weighting sample points in dependence of the samples along the integration path. In this work we propose a solution for a special class of problems, namely the extraction and emphasis of contours in volumetric datasets. The accuracy of the illumination of the extracted contours can be derived in an exact manner. Main applications of our method include contour extraction and enhancement of features, noise removal and revealing of important spatial relationships between interior and exterior structures, making it an attractive tool for improved X-ray-like investigations of the given dataset.

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Fourier volume rendering

Cited by 178 publications

References 9 publications

Virtual Colonoscopy - Technical Aspects

Virtual Colonoscopy - Technical Aspects

Two methods for wavelet-based volume rendering

Enhancing Fourier Volume Rendering Using Contour Extraction

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