Segmenting the visible human female.
Identifieur interne : 001856 ( PubMed/Corpus ); précédent : 001855; suivant : 001857Segmenting the visible human female.
Auteurs : Ameya Malvankar ; Bharti TemkinSource :
- Studies in health technology and informatics [ 0926-9630 ] ; 2006.
English descriptors
- KwdEn :
- MESH :
- geographic : United States.
- Female, Humans, Imaging, Three-Dimensional, Internet, Models, Anatomic, User-Computer Interface.
Abstract
Web-based three-dimensional Virtual Body Structures (W3D-VBS) is an interactive image-based anatomical training system over the Internet. It uses segmented low-resolution Visible Human Male (LR-VHM) data to dynamically explore, select, highlight, label, extract, manipulate, and stereoscopically palpate 3D virtual anatomical models with a haptic device. The segmentation results presented in this paper for the Visible Human Female (VHF) and the high resolution Visible Human Male (HR-VHM) have been obtained using our segmentation tools. Segmenting the HR-VHM was an easier task as we use the segmented shapes and label information of existing LR-VHM data, with the same image content. This is not the case for the VHF and we needed to develop a special tool, Segm-VHF, which allows us to integrate the VHF dataset into W3D-VBS.
PubMed: 16404078
Links to Exploration step
pubmed:16404078Le document en format XML
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It uses segmented low-resolution Visible Human Male (LR-VHM) data to dynamically explore, select, highlight, label, extract, manipulate, and stereoscopically palpate 3D virtual anatomical models with a haptic device. The segmentation results presented in this paper for the Visible Human Female (VHF) and the high resolution Visible Human Male (HR-VHM) have been obtained using our segmentation tools. Segmenting the HR-VHM was an easier task as we use the segmented shapes and label information of existing LR-VHM data, with the same image content. This is not the case for the VHF and we needed to develop a special tool, Segm-VHF, which allows us to integrate the VHF dataset into W3D-VBS.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">16404078</PMID><DateCreated><Year>2006</Year><Month>01</Month><Day>11</Day></DateCreated><DateCompleted><Year>2006</Year><Month>04</Month><Day>17</Day></DateCompleted><Article PubModel="Print"><Journal><ISSN IssnType="Print">0926-9630</ISSN><JournalIssue CitedMedium="Print"><Volume>119</Volume><PubDate><Year>2006</Year></PubDate></JournalIssue><Title>Studies in health technology and informatics</Title><ISOAbbreviation>Stud Health Technol Inform</ISOAbbreviation></Journal><ArticleTitle>Segmenting the visible human female.</ArticleTitle><Pagination><MedlinePgn>361-3</MedlinePgn></Pagination><Abstract><AbstractText>Web-based three-dimensional Virtual Body Structures (W3D-VBS) is an interactive image-based anatomical training system over the Internet. It uses segmented low-resolution Visible Human Male (LR-VHM) data to dynamically explore, select, highlight, label, extract, manipulate, and stereoscopically palpate 3D virtual anatomical models with a haptic device. The segmentation results presented in this paper for the Visible Human Female (VHF) and the high resolution Visible Human Male (HR-VHM) have been obtained using our segmentation tools. Segmenting the HR-VHM was an easier task as we use the segmented shapes and label information of existing LR-VHM data, with the same image content. This is not the case for the VHF and we needed to develop a special tool, Segm-VHF, which allows us to integrate the VHF dataset into W3D-VBS.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Malvankar</LastName><ForeName>Ameya</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Department of Computer Science, Texas Tech University, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Temkin</LastName><ForeName>Bharti</ForeName><Initials>B</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>Stud Health Technol Inform</MedlineTA><NlmUniqueID>9214582</NlmUniqueID><ISSNLinking>0926-9630</ISSNLinking></MedlineJournalInfo><CitationSubset>T</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName MajorTopicYN="N" UI="D005260">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D006801">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D021621">Imaging, Three-Dimensional</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D020407">Internet</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="Y" UI="D008953">Models, Anatomic</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" Type="Geographic" UI="D014481">United States</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D014584">User-Computer Interface</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="pubmed"><Year>2006</Year><Month>1</Month><Day>13</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2006</Year><Month>4</Month><Day>18</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2006</Year><Month>1</Month><Day>13</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">16404078</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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