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Fig 1.

Illustration of the emission-absorption model used to compute the color of a pixel.

A ray is cast from the virtual camera through the pixel in the image plane. The intersection with the volume is found and the volume is sampled at regular interval, the sample value is mapped to optical properties which are composited to obtain the pixel color.

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Fig 2.

Illustration of the 2-pass volume rendering algorithm implemented in PRISM.

In the first pass, the front and back faces of the bounding box of the volume are rendered in two separate textures as illustrated in (a) and (b). The color assigned to the bounding box vertices encodes the normalized coordinate of the vertices in the volume. The box is clipped using near and far clipping planes of the renderer to avoid creating holes in the image. In the second pass, textures (a) and (b) are used to compute ray equation and run the integration. Bounds of the ray are adjusted using depth buffer accumulated by VTK for the rendering of other primitives, in this case, the 3D surface of a tumor (c). Doing so allows the correct interleaving of surfaces and volumes as shown in (d).

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Table 1.

Comparison of the frame rates obtained with the VTK GPU raycast volume renderer and the PRISM framework with and without the early ray termination (ETR) optimization with an alpha threshold of 0.99.

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Fig 3.

A 320x320x280 voxel volume rendered using the default modes.

a) the VTK GPU raycast volume renderer, b) the flexible PRISM GPU raycast framework and c) the PRISM framework with early ray termination (ERT).

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Fig 4.

Illustration of volume carving and opacity peeling methods.

(a) Original MRI volume, (b) Volume Carving with a spherical tool, (c) Opacity peeling where the first layer is peeled off.

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Fig 5.

Decluttering an angiographic CT to highlight the structure of interest, an AVM.

(a) The original CTA volume rendered with Blinn-Phong shading. (b) A volume containing the topological distance to the AVM for each voxel. (c) The decluttered image obtained by combining (a) and (b).

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Fig 6.

Chroma-depth volume contribution shader used with 3 different color transfer function produces.

(a)Chroma-depth, (b)Pseudo chroma-depth and (c)Aerial perspective.

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Fig 7.

Edge enhancement of an angiographic CT.

The volume is rendered with (a) only the edge rendering shader, (b) Only a Blinn-Phong shader, (c) Edge and Blinn-Phong shader combined.

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Fig 8.

Blood flow depiction.

(a) The original CTA volume rendered with Blinn-Phong shading. (b) Volume containing precomputed blood flow information, i.e. distance, within vessels, between entry and exit of blood from the brain. (c) Volume from (b) combined with (a) using the Volume shader of Algorithm 6. When the time parameter is updated to render each frame, the waves move along the vessels in the direction of the blood flow as illustrated in the accompanying video (S1 Video).

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Table 2.

Frame rate in frames per second (fps) for the different volume rendering examples presented in this paper.

Note that pseudo chroma-depth and aerial perspective are not listed as they differ from chroma-depth only in the content of the transfer function and not in the computation. In practice the frame rate difference was not measurable.

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Table 3.

Mean and standard deviation of the answers provided by the users on the online questionnaire.

Each question is answered on a scale of 1 to 5 (1 = strongly disagree, 5 = strongly agree). The System Usability Scale (SUS) score (last line of part 2) is obtained by subtracting 1 from the score of each odd-numbered question and subtracting the score of even-numbered from 5. We sum the results obtained for each question and multiply by 2.5 to obtain the final score.

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