[Retracted] Hippocampus Segmentation Method Based on Subspace Patch-Sparsity Clustering in Noisy Brain MRI

Table 1

Quantitative results for comparison models in different noises.

σ		SSC	LRR	Fuzzy GMM	LSM	U-Net	Proposed
5	FNR	0.461	0.407	0.461	0.512	0.523	0.453
	RSE	0.082	0.089	0.099	0.182	0.181	0.089
	DSC	0.761	0.808	0.891	0.782	0.831	0.903
10	FNR	0.357	0.543	0.504	0.516	0.621	0.707
	RSE	0.075	0.087	0.098	0.078	0.086	0.060
	DSC	0.682	0.836	0.718	0.805	0.816	0.836
20	FNR	0.316	0.593	0.623	0.485	0.707	0.718
	RSE	0.068	0.067	0.070	0.072	0.074	0.064
	DSC	0.579	0.531	0.690	0.734	0.752	0.792
30	FNR	0.297	0.282	0.317	0.378	0.322	0.252
	RSE	0.050	0.063	0.052	0.036	0.060	0.044
	DSC	0.508	0.471	0.523	0.658	0.680	0.697