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. Author manuscript; available in PMC: 2017 Jun 1.
Published in final edited form as: IEEE J Sel Top Signal Process. 2016 Mar 23;10(4):672–687. doi: 10.1109/JSTSP.2016.2545518

Fig. 10.

Fig. 10

Multi-scale low rank versus low rank + sparse decomposition on a dynamic contrast enhanced magnetic resonance image series. For the multi-scale result, small contrast dynamics in vessels are captured in 4 × 4 blocks while contrast dynamics in the liver are captured in 16 × 16 blocks. The biggest block size captures the static tissues and interestingly the respiratory motion. In contrast, the low rank + sparse modeling could only provide a coarse separation of dynamics and static tissue, which result in neither truly sparse nor truly low rank components.