Matches in SemOpenAlex for { <https://semopenalex.org/work/W2284374992> ?p ?o ?g. }
Showing items 1 to 94 of
94
with 100 items per page.
- W2284374992 endingPage "353" @default.
- W2284374992 startingPage "346" @default.
- W2284374992 abstract "Low-dose CT-like imaging systems offer numerous perspectives in terms of clinical application, in particular for osteoarticular diseases. In this paper, we address the challenging problem of 3D femur modeling and estimation from bi-planar views. Our contributions are threefold. First, we propose a non-uniform hierarchical decomposition of the shape prior of increasing clinical-relevant precision which is achieved through curvature driven unsupervised clustering acting on the geodesic distances between vertices. Second, we introduce a graphical-model representation of the femur which can be learned from a small number of training examples and involves third-order and fourth-order priors, while being similarity and mirror-symmetry invariant and providing means of measuring regional and boundary supports in the bi-planar views. Last but not least, we adopt an efficient dual-decomposition optimization approach for efficient inference of the 3D femur configuration from bi-planar views. Promising results demonstrate the potential of our method." @default.
- W2284374992 created "2016-06-24" @default.
- W2284374992 creator A5010516895 @default.
- W2284374992 creator A5055177125 @default.
- W2284374992 creator A5077223134 @default.
- W2284374992 creator A5082779714 @default.
- W2284374992 creator A5085451251 @default.
- W2284374992 date "2011-01-01" @default.
- W2284374992 modified "2023-10-08" @default.
- W2284374992 title "Pose-Invariant 3D Proximal Femur Estimation through Bi-planar Image Segmentation with Hierarchical Higher-Order Graph-Based Priors" @default.
- W2284374992 cites W1554965040 @default.
- W2284374992 cites W1970053289 @default.
- W2284374992 cites W1998440626 @default.
- W2284374992 cites W2000947447 @default.
- W2284374992 cites W2060247851 @default.
- W2284374992 cites W2104276184 @default.
- W2284374992 cites W2114741181 @default.
- W2284374992 cites W2118961645 @default.
- W2284374992 cites W2154962100 @default.
- W2284374992 doi "https://doi.org/10.1007/978-3-642-23626-6_43" @default.
- W2284374992 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/22003718" @default.
- W2284374992 hasPublicationYear "2011" @default.
- W2284374992 type Work @default.
- W2284374992 sameAs 2284374992 @default.
- W2284374992 citedByCount "2" @default.
- W2284374992 countsByYear W22843749922014 @default.
- W2284374992 crossrefType "book-chapter" @default.
- W2284374992 hasAuthorship W2284374992A5010516895 @default.
- W2284374992 hasAuthorship W2284374992A5055177125 @default.
- W2284374992 hasAuthorship W2284374992A5077223134 @default.
- W2284374992 hasAuthorship W2284374992A5082779714 @default.
- W2284374992 hasAuthorship W2284374992A5085451251 @default.
- W2284374992 hasBestOaLocation W22843749921 @default.
- W2284374992 hasConcept C105611402 @default.
- W2284374992 hasConcept C107673813 @default.
- W2284374992 hasConcept C121684516 @default.
- W2284374992 hasConcept C134786449 @default.
- W2284374992 hasConcept C153180895 @default.
- W2284374992 hasConcept C154945302 @default.
- W2284374992 hasConcept C165818556 @default.
- W2284374992 hasConcept C177769412 @default.
- W2284374992 hasConcept C190470478 @default.
- W2284374992 hasConcept C195065555 @default.
- W2284374992 hasConcept C2524010 @default.
- W2284374992 hasConcept C2776214188 @default.
- W2284374992 hasConcept C31972630 @default.
- W2284374992 hasConcept C33923547 @default.
- W2284374992 hasConcept C37914503 @default.
- W2284374992 hasConcept C41008148 @default.
- W2284374992 hasConcept C73555534 @default.
- W2284374992 hasConcept C89600930 @default.
- W2284374992 hasConcept C92835128 @default.
- W2284374992 hasConceptScore W2284374992C105611402 @default.
- W2284374992 hasConceptScore W2284374992C107673813 @default.
- W2284374992 hasConceptScore W2284374992C121684516 @default.
- W2284374992 hasConceptScore W2284374992C134786449 @default.
- W2284374992 hasConceptScore W2284374992C153180895 @default.
- W2284374992 hasConceptScore W2284374992C154945302 @default.
- W2284374992 hasConceptScore W2284374992C165818556 @default.
- W2284374992 hasConceptScore W2284374992C177769412 @default.
- W2284374992 hasConceptScore W2284374992C190470478 @default.
- W2284374992 hasConceptScore W2284374992C195065555 @default.
- W2284374992 hasConceptScore W2284374992C2524010 @default.
- W2284374992 hasConceptScore W2284374992C2776214188 @default.
- W2284374992 hasConceptScore W2284374992C31972630 @default.
- W2284374992 hasConceptScore W2284374992C33923547 @default.
- W2284374992 hasConceptScore W2284374992C37914503 @default.
- W2284374992 hasConceptScore W2284374992C41008148 @default.
- W2284374992 hasConceptScore W2284374992C73555534 @default.
- W2284374992 hasConceptScore W2284374992C89600930 @default.
- W2284374992 hasConceptScore W2284374992C92835128 @default.
- W2284374992 hasLocation W22843749921 @default.
- W2284374992 hasLocation W22843749922 @default.
- W2284374992 hasLocation W22843749923 @default.
- W2284374992 hasLocation W22843749924 @default.
- W2284374992 hasLocation W22843749925 @default.
- W2284374992 hasOpenAccess W2284374992 @default.
- W2284374992 hasPrimaryLocation W22843749921 @default.
- W2284374992 hasRelatedWork W1989705029 @default.
- W2284374992 hasRelatedWork W2029790457 @default.
- W2284374992 hasRelatedWork W2085259108 @default.
- W2284374992 hasRelatedWork W2580650124 @default.
- W2284374992 hasRelatedWork W2968424575 @default.
- W2284374992 hasRelatedWork W3041320102 @default.
- W2284374992 hasRelatedWork W3122088529 @default.
- W2284374992 hasRelatedWork W3142333283 @default.
- W2284374992 hasRelatedWork W3181673064 @default.
- W2284374992 hasRelatedWork W4386190339 @default.
- W2284374992 isParatext "false" @default.
- W2284374992 isRetracted "false" @default.
- W2284374992 magId "2284374992" @default.
- W2284374992 workType "book-chapter" @default.