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identifier TX T0 DP 7(The) acceleration techniques for Fast Volume Rendering1997
Y ȐĬYtTŐYP YMasterMaster's Thesis
Medical images of CT or MRI are reconstructed to 3D volume rendering images. This is called Volume Visualization. Existing Visualization algorithms have some problems. They are the time of visualizing. Complex visualizing algorithm has the complex computation. It is the cause of slow visualizing.
Volume Visualization has the two type of algorithm. They are the image-order visualization and the object-order visualization. RayCasting is the image-order visualization algorithm. It is independent on the volume size. But it needs the time of memory relocation. Splatting is the object-order visualization algorithm. It is dependent on the volume size. But it doesn't need the time memory relocation. Both of them cost the huge time of rendering.
Volume Visualization need the high quality of the image and the fast speed of rendering, simultaneously. But they are in the relationship of tradeoff. The solution is not easy.
This thesis applies some of speed-up techniques in the volume visualization algorithm. The speed-up techniques are hybrid-redering, classification using octree or RunLengthEncoding. The first technique is the combination of RayCasing and Splatting. The result has the merit of them. The second and the third techniques apply in the couse of classification. They result in compression of the volume data. And so they can speed-up the rendering. But they need the extra data structures and is dependent on the coherence of the voxels.
The combination of the three techniques is possible. This thesis compares the effect between the combination algorithms. Especially, the author focus on the image quality and the time.
ShearWarp of hybrid rendering is effective in high image quality. Octree and RLE are effective in speedy rendering. But the latter need the extra memory and time for constructing of data structures.;XYթ 5 D 3( <\ l1X 0 <\ T XՔ 0t XX T 0@ 8D . TX \x 0x RayCastingX pt0X l0 ųx t T ȥ pt0X X@ Ĭ 8XՔ pt0X |XX J0 L8 X T X Ĭt DՔX. tǃ@ TX ĳ| XՔ xt . TX \x 0x SplattingX Ɣ XՔ pt0X @ T ȥ pt0X X ٳ|X X X Ĭt DՔX J̹ <\ ĬD h<\ pt0X l0 ] TX ĳĳ hخ $Ɍ .
XY Ŕ @ X @ hخ `x T ĳ l. 췘 X D t0 t \ t t\ @ TX ĳ| XՔ xt \ X TX ĳŔ Ҙtܴ$(TradOff)X Ĭ 1 . ĳ lX P D ٳ ̹q ¤Д T 0t l \ l| ̹q¤Д l\ TX T 0t X. |8 l\ T 0@ T Ĭ ĬX ĳ| T T D 貕¤Д )t, @X ,҅ĳ| XՔ tИ<tX(Classification) Ĭ ,҅ @D T Ĭ x¤Д RLE(RunLengthEncoding)0 %ƸҬ(Octree) 0D lX 2( <\ TXՔ T Ĭ 0tX T 0X ̹D $\ Xtܴ 0x ShearWarping X lX. t\ 0@ X X D Xt ȴ TX ĳ| `t h<\ P lmD ٳ ̹q¤Д 0t.~http://dspace.ewha.ac.kr/handle/2015.oak/198653;
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