Multiple Blur Images Restoration -- A Parallel Computing Approach

2012 ◽  
Author(s):  
Sudha Tiwari ◽  
Naazish Rahim ◽  
Sandeep Sahu ◽  
Nikita Sharma
Keyword(s):  
Parallel Computing ◽  
Computing Approach

A parallel computing approach to genetic sequence comparison: The master-worker paradigm with interworker communication

1991 ◽  
Vol 24 (2) ◽  
pp. 152-169 ◽  
Author(s):  
Dean F. Sittig ◽  
David Foulser ◽  
Nicholas Carriero ◽  
George McCorkle ◽  
Perry L. Miller
Keyword(s):  
Parallel Computing ◽  
Sequence Comparison ◽  
Genetic Sequence ◽  
Computing Approach

scholarly journals An Ultra-Fast Digitally Reconstructed Radiograph (DRR) Implementation of the Siddon-Jacobs Algorithm using Parallel Computing: Runtime Improvement of an Intensity-Based 2D/3D Registration

2021 ◽  
Vol 7 (2) ◽  
pp. 25-28
Author(s):  
Julio C. Alvarez-Gomez ◽  
Gerardo Jimenez Palavicini ◽  
Hubert Roth ◽  
Jürgen Wahrburg
Keyword(s):  
Parallel Computing ◽  
3D Registration ◽  
3D Data ◽  
Pixel Location ◽  
Mri Scans ◽  
Computing Approach ◽  
Ct And Mri

Abstract A key component of an intensity-based 2D/3D registration is the digitally reconstructed radiograph (DRR) module, which creates 2D projections from pre-operative 3D data, e.g., CT and MRI scans. On average, an intensity-based 2D/3D registration requires ten iterations and the rendering of twelve DRR images per iteration. In a typical DRR implementation, the rendering time is about two seconds, and the registration runtime is four minutes. We present an implementation of the Siddon-Jacobs algorithm that uses a novel pixel-step approach to determine the pixel location of the rendering plane. In addition, we calculate the intensity of each pixel in the rendering plane using a parallel computing approach. The DRR rendering time is reduced to 10ms on average so that the registration runtime can be achieved in an average of 4.8 seconds.

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