scholarly journals Hardware Acceleration of Image Registration Algorithm on FPGA-based Systems on Chip

2019 ◽  
Author(s):  
Ioannis Stratakos ◽  
Dimitrios Gourounas ◽  
Vasileios Tsoutsouras ◽  
Theodore Economopoulos ◽  
George Matsopoulos ◽  
...  
Keyword(s):  
Image Registration ◽  
Hardware Acceleration ◽  
Registration Algorithm ◽  
Systems On Chip ◽  
Image Registration Algorithm ◽  
On Chip

scholarly journals Optimizing MRI Registration using Software/Hardware Co-Design Model on FPGA

2020 ◽  
Vol 10 (2) ◽  
pp. 128-137
Author(s):  
Yasmeen Farouk ◽  
Sherine Rady
Keyword(s):  
Image Registration ◽  
Statistical Parametric Mapping ◽  
Hardware Acceleration ◽  
Software Tool ◽  
Design Model ◽  
Analytical Technique ◽  
Registration Algorithm ◽  
Image Registration Algorithm ◽  
Field Programmable ◽  
Diffeomorphic Image Registration

The correct localization of brain tissue deformation and determination of the tumor growth relies majorly on the accuracy of the process known by image registration. Poor registration may lead to misclassified diseases and highly affect image-guided surgery and radiation therapies. Voxel-based morphometry (VBM) is an image analytical technique encompassing accurate registration but suffers from intensive time computations, similar to most of image registration techniques. Achieving the compromise between accuracy and computations is a challenging mission. Field programmable gate arrays have fast-evolving and customizable hardware acceleration capabilities that promise to help speed up computational tasks. This paper presents a software/hardware co-design model for accelerating the implementation of the diffeomorphic image registration algorithm ‘DARTEL’ as a part of VBM that analyzes MRI images. An optimized and pipelined hardware architecture is proposed and integrated into the Statistical Parametric Mapping (SPM) software tool that runs the DARTEL. Acceleration of the DARTEL registration algorithm resulted in a speedup factor of 114x on function-level, compared to the CPU with a contribution of 8x faster for the overall performance in the registration process of the SPM. The proposed model is successfully validated for the identification of Alzheimer’s disease based on T1-weighted MRI. A proposed software/hardware co-design model for VBM achieves remarkable acceleration while maintaining classification accuracy and proving proficiency against other CPU and GPU implementations.

SAR Image Registration Using Ratio Mutual Information

2012 ◽  
Vol 241-244 ◽  
pp. 2630-2637
Author(s):  
Chun Rong Wei ◽  
Chu He ◽  
Hong Sun
Keyword(s):  
Image Registration ◽  
Mutual Information ◽  
Speckle Noise ◽  
Synthetic Aperture Radar Image ◽  
Reference Image ◽  
Sar Image ◽  
Local Maxima ◽  
Characteristic Quantity ◽  
Registration Algorithm ◽  
Image Registration Algorithm

In order to reduce the noise sensitivity of the SAR (synthetic aperture radar) image registration, a image registration algorithm which basing on the ratio mutual information (RatioMI) is proposed in this paper. Firstly, the ratio images of the reference image and the floating image are gotten by using the ratio operator, and then take the two ratio images as a similar characteristic quantity to construct the similarity measure function which was used in the optimization process of the image registration experiment. The experimental results of the SAR image registration show that the new registration algorithm which based on the RatioMI is effectively in avoiding the local maxima point problems causing by speckle noise.

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