Voxel-Based Interactive Rendering of Translucent Materials under Area Lights Using Sparse Samples

Digitally reconstructed radiograph (DRR) from CT volumetric data has been used in numerous medical applications such as 3D treatment planning and CT-to-fluoroscopic alignment. The poor efficiency of the DRR generation is the main problem in such applications. Many researches have been attempted to accelerate the DRR calculation. However, the performance and precision cannot be achieved without the sacrifice of one or the other. In this study, a fast and high precision DRR generation method is proposed on a consumer PC platform. Instead of using CPU, the method takes the advantages of the powerful parallel computation and flexible programming capability of the graphic processing unit (GPU) to reach almost interactive rendering rate while maintaining 12-bit precision of the original CT data. This method can generate DRR images at 4.6 frames per second using 512 × 512 × 261 dataset in the 512 × 512 view port, and its precision is compatible to that generated by the CPU-based method. Besides, in order to simulate clinical radiograph images, a compensation filter is implemented in the DRR generation to compensate varying thickness of bone structures. The additional compensation filter can achieve a DRR image with more uniform optical density but takes no obvious performance overhead.

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Analysis of a complete DNA–protein affinity landscape

Journal of The Royal Society Interface ◽

10.1098/rsif.2009.0193 ◽

2009 ◽

Vol 7 (44) ◽

pp. 397-408 ◽

Cited By ~ 42

Author(s):

William Rowe ◽

Mark Platt ◽

David C. Wedge ◽

Philip J. Day ◽

Douglas B. Kell ◽

...

Keyword(s):

Life Sciences ◽

Fitness Landscapes ◽

Local Optima ◽

Binding Profile ◽

Fine Grained ◽

Protein Affinity ◽

Experimental Variation ◽

Sparse Samples ◽

On Chip ◽

Wide Sector

Properties of biological fitness landscapes are of interest to a wide sector of the life sciences, from ecology to genetics to synthetic biology. For biomolecular fitness landscapes, the information we currently possess comes primarily from two sources: sparse samples obtained from directed evolution experiments; and more fine-grained but less authentic information from ‘ in silico ’ models (such as NK -landscapes). Here we present the entire protein-binding profile of all variants of a nucleic acid oligomer 10 bases in length, which we have obtained experimentally by a series of highly parallel on-chip assays. The resulting complete landscape of sequence-binding pairs, comprising more than one million binding measurements in duplicate, has been analysed statistically using a number of metrics commonly applied to synthetic landscapes. These metrics show that the landscape is rugged, with many local optima, and that this arises from a combination of experimental variation and the natural structural properties of the oligonucleotides.

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