Searching across hundreds of databases
Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
URL: http://www.nitrc.org/projects/lll/
Proper Citation: Local Label Learning Segmentation (RRID:SCR_009504)
Description: Software using a novel local label learning strategy to estimate the target image?s segmentation label using statistical machine learning techniques. They used a support vector machine (SVM) with a K nearest neighbor (KNN) based training sample selection strategy to learn a classifier for each of the target image voxel based on a training dataset consisting of its neighboring voxels in the atlases. Validation experiments on hippocampus segmentation of 117 MR images demonstrated that the method can produce segmentation results consistently better than state-of-the-art label fusion methods.
Abbreviations: LLL Segmentation
Synonyms: Local Label Learning (LLL) Segmentation
Resource Type: software resource, segmentation software, data processing software, software application, image analysis software
Defining Citation: PMID:24151008
Keywords: magnetic resonance, svm, segmentation, local label learning, multi-atlas based segmentation
Expand Allis listed by |
|
has parent organization |
We found {{ ctrl2.mentions.total_count }} mentions in open access literature.
We have not found any literature mentions for this resource.
We are searching literature mentions for this resource.
Most recent articles:
{{ mention._source.dc.creators[0].familyName }} {{ mention._source.dc.creators[0].initials }}, et al. ({{ mention._source.dc.publicationYear }}) {{ mention._source.dc.title }} {{ mention._source.dc.publishers[0].name }}, {{ mention._source.dc.publishers[0].volume }}({{ mention._source.dc.publishers[0].issue }}), {{ mention._source.dc.publishers[0].pagination }}. (PMID:{{ mention._id.replace('PMID:', '') }})
Check
for all resource mentions.
A list of researchers who have used the resource and an author search tool
A list of researchers who have used the resource and an author search tool. This is available for resources that have literature mentions.
No rating or validation information has been found for Local Label Learning Segmentation.
No alerts have been found for Local Label Learning Segmentation.
Source: SciCrunch Registry
Welcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
