ArticleComputational and mathematical methods in medicine2012
Bayes clustering and structural support vector machines for segmentation of carotid artery plaques in multicontrast MRI.
Article in Computational and mathematical methods in medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Carotid atherosclerotic plaque segmentation in multi-weighted MRI using a two-stage neural network: advantages of training with high-resolution imaging and histology.Frontiers in cardiovascular medicine · 2023Article
- Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: a narrative review for stroke application.Annals of translational medicine · 2021Review
- Retracted: Bayes clustering and structural support vector machines for segmentation of carotid artery plaques in multicontrast MRI.Computational and mathematical methods in medicine · 2014Article
- Thresholded two-phase test sample representation for outlier rejection in biological recognition.Computational and mathematical methods in medicine · 2013Article
- Selective segmentation for global optimization of depth estimation in complex scenes.TheScientificWorldJournal · 2013Article
Corrections and comments
- Retraction · 2014-03-10Notice - Limited or No Information · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate segmentation of carotid artery plaque in MR images is not only a key part but also an essential step for in vivo plaque analysis. Due to the indistinct MR images, it is very difficult to implement the automatic segmentation. Two kinds of classification models, that is, Bayes clustering and SSVM, are introduced in this paper to segment the internal lumen wall of carotid artery. The comparative experimental results show the segmentation performance of SSVM is better than Bayes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.