Improved Implementation of Expectation Maximization Algorithm on Graphic Processing Unit

2018 ◽  
pp. 623-629
Author(s):  
Si-Yuan Jing ◽  
Rui Sun ◽  
Chun-Ming Xie ◽  
Peng Jin ◽  
Yi Liu ◽  
...  
Keyword(s):  
Expectation Maximization ◽  
Graphic Processing Unit ◽  
Expectation Maximization Algorithm ◽  
Processing Unit ◽  
Graphic Processing

Partially Coherent Beam Real-Time Generation Method Accelerated by Graphic Processing Unit

2016 ◽  
Vol 45 (3) ◽  
pp. 310001 ◽  
Author(s):  
倪小龙 NI Xiao-long ◽  
刘智 LIU Zhi ◽  
姜会林 JIANG Hui-lin ◽  
陈纯毅 CHEN Chun-yi ◽  
刘艺 LIU Yi ◽  
...  
Keyword(s):  
Real Time ◽  
Graphic Processing Unit ◽  
Coherent Beam ◽  
Processing Unit ◽  
Partially Coherent ◽  
Graphic Processing

scholarly journals Improved Implementation of Simulation for Membrane Computing on the Graphic Processing Unit

2013 ◽  
Vol 11 ◽  
pp. 184-190 ◽  
Author(s):  
Ali Maroosi ◽  
Ravie Chandren Muniyandi ◽  
Elankovan A. Sundararajan ◽  
Abdullah Mohd Zin
Keyword(s):  
Membrane Computing ◽  
Graphic Processing Unit ◽  
Processing Unit ◽  
Graphic Processing

FAST AND HIGH PRECISION DIGITALLY RECONSTRUCTED RADIOGRAPH GENERATION ON GRAPHIC PROCESSING UNIT

2012 ◽  
Vol 24 (01) ◽  
pp. 9-15 ◽  
Author(s):  
Chi-Lin Yang ◽  
Been-Der Yang ◽  
Jaw-Lin Wang
Keyword(s):  
High Precision ◽  
Graphic Processing Unit ◽  
Processing Unit ◽  
Interactive Rendering ◽  
Varying Thickness ◽  
Ct Data ◽  
Bone Structures ◽  
Flexible Programming ◽  
The Sacrifice ◽  
Graphic Processing

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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