Haptic editing of MRI brain data.
Identifieur interne : 001E96 ( Ncbi/Merge ); précédent : 001E95; suivant : 001E97Haptic editing of MRI brain data.
Auteurs : Alexei Sourin [Singapour] ; Shamima YasminSource :
- Studies in health technology and informatics [ 0926-9630 ] ; 2012.
English descriptors
- KwdEn :
- MESH :
- methods : Image Enhancement.
- pathology : Brain.
- Humans, Magnetic Resonance Imaging, Touch Perception, User-Computer Interface.
Abstract
Automated brain segmentation may leave errors which can be identified by comparing the location of the actual MRI voxels with reference to the reconstructed pial polygonal surface of the brain. Location of the segmentation errors can be marked by displaying color spots on the brain surface followed by its interactive editing, as we previously proposed. In this paper, a new haptic friction-based approach of identifying and correcting errors has been discussed. The user can feel as different friction the discrepancy along the reconstructed surface by moving a haptic proxy along it followed by rubbing the surface as if it is being polished. The proposed approach does not only limit its application in editing of medical data, but can also be successfully used for visually impaired group as this dynamic friction-based editing helps any novice user identify error prone area just by touching the surface.
PubMed: 22357042
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pubmed:22357042Le document en format XML
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Location of the segmentation errors can be marked by displaying color spots on the brain surface followed by its interactive editing, as we previously proposed. In this paper, a new haptic friction-based approach of identifying and correcting errors has been discussed. The user can feel as different friction the discrepancy along the reconstructed surface by moving a haptic proxy along it followed by rubbing the surface as if it is being polished. The proposed approach does not only limit its application in editing of medical data, but can also be successfully used for visually impaired group as this dynamic friction-based editing helps any novice user identify error prone area just by touching the surface.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">22357042</PMID><DateCreated><Year>2012</Year><Month>02</Month><Day>23</Day></DateCreated><DateCompleted><Year>2012</Year><Month>05</Month><Day>08</Day></DateCompleted><Article PubModel="Print"><Journal><ISSN IssnType="Print">0926-9630</ISSN><JournalIssue CitedMedium="Print"><Volume>173</Volume><PubDate><Year>2012</Year></PubDate></JournalIssue><Title>Studies in health technology and informatics</Title><ISOAbbreviation>Stud Health Technol Inform</ISOAbbreviation></Journal><ArticleTitle>Haptic editing of MRI brain data.</ArticleTitle><Pagination><MedlinePgn>490-6</MedlinePgn></Pagination><Abstract><AbstractText>Automated brain segmentation may leave errors which can be identified by comparing the location of the actual MRI voxels with reference to the reconstructed pial polygonal surface of the brain. Location of the segmentation errors can be marked by displaying color spots on the brain surface followed by its interactive editing, as we previously proposed. In this paper, a new haptic friction-based approach of identifying and correcting errors has been discussed. The user can feel as different friction the discrepancy along the reconstructed surface by moving a haptic proxy along it followed by rubbing the surface as if it is being polished. 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