Search Results for "compression algorithm"

***Please note that a much improved Version can be found on Github:*** https://github.com/sOrzada/VOP_Compression Here we introduce to algorithms for post-processing of VOP sets. Algorithm 1 reduces the Overestimation for a given set of VOPs. Especially useful to reduce the overestimation in VOP sets calculated with the compression algorithms by Lee et al. and Orzada et al. Algorithm 2 tests a given set of VOPs for redundancy. It can be used to reduce the number of VOPs in a dataset produced by Eichfelder and Gebhardt's algorithm. ...

***Please note that a much improved Version can be found on Github:*** https://github.com/sOrzada/VOP_Compression This work is described in: Orzada S, Fielder TM, Quick HH, Ladd ME, "A local SAR compression algorithm with improved compression, speed and flexibility", https://doi.org/10.1002/mrm.28739. This new algorithm is an iterative expansion of the exisisting local SAR compression algorithm for MRI proposed by Lee et al. ( https://doi.org/10.1002/mrm.23140) The number of VOPs is approximately halved with the new algorithm, while at the same time the compression time is reduced with speed-up factors of up to 2.5.

**** This work is outdated! For better compression and speed use these: ***** https://github.com/sOrzada/VOP_Compression Virtual Observation Points SAR compression. Contains multiple Algorithms: Compression according to Eichfelder et al. and Lee et al. The Lee algorithm is enhanced by including overestimation control to reduce maximum relative overestimation. All algorithms are implemented in Matlab and were optimized for enhanced speed.