Mar 7, 2018 · Automatic and accurate segmentation of hippocampal structures in medical images is of great importance in neuroscience studies.
In the experiments, we evaluate our proposed method by conducting hippocampus segmentation using the ADNI dataset. Both the qualitative and quantitative results ...
Automatic and accurate segmentation of hippocampal structures in medical images is of great importance in neuroscience studies. In multi-atlas based.
To solve this problem, we propose a patch-based label fusion with structured discriminant embedding method to automatically segment the hippocampal structure ...
Bibliographic details on Patch-Based Label Fusion with Structured Discriminant Embedding for Hippocampus Segmentation.
This work introduces a patch-based label fusion approach for MRI segmentation, considering enhanced specificity and sensitivity thresholding, termed Patch-based ...
In this work, a novel multi-atlas patch based label fusion method is developed for the segmentation of hippocampus. Most previously PBM methods select ...
Missing: Discriminant | Show results with:Discriminant
This process can enhance discrimination of features for different local regions in the anatomical structure. Finally, based on extracted discriminant features, ...
In this paper, an automatic labeling method is developed to segment the hippocampus from brain MR images. It is a patch embedding multi-atlas label fusion ...
Missing: Discriminant | Show results with:Discriminant
The proposed label fusion method combines the advantages of label fusion methods based on sparse representation (SRLF) and weighted voting methods using ...