Virtual 2D-3D Fracture Reduction with Bone Length Recovery Using Statistical Shape Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F18%3A63520244" target="_blank" >RIV/70883521:28140/18:63520244 - isvavai.cz</a>
Alternative codes found
RIV/00216224:14310/18:00106612 RIV/00216305:26230/18:PU130775 RIV/00843989:_____/18:E0107978
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-04747-4_20" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-04747-4_20</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-04747-4_20" target="_blank" >10.1007/978-3-030-04747-4_20</a>
Alternative languages
Result language
angličtina
Original language name
Virtual 2D-3D Fracture Reduction with Bone Length Recovery Using Statistical Shape Models
Original language description
Computer-assisted 3D preoperative planning based on 2D stereo radiographs has been brought into focus recently in the field of orthopedic surgery. To enable planning, it is crucial to reconstruct a patient-specific 3D bone model from X-ray images. However, most of the existing studies deal only with uninjured bones, which limits their possible applications for planning. In this paper, we propose a method for the reconstruction of long bones with diaphyseal fractures from 2D radiographs of the individual fracture segments to 3D polygonal models of the intact bones. In comparison with previous studies, the main contribution is the ability to recover an accurate length of the target bone. The reconstruction is based on non-rigid 2D-3D registration of a single statistical shape model onto the radiographs of individual fragments, performed simultaneously with the virtual fracture reduction. The method was tested on a syntethic data set containing 96 virtual fractures and on real radiographs of dry cadaveric bones suffering peri-mortem injuries. The accuracy was evaluated using the Hausdorff distance between the reconstructed and ground-truth bone models. On the synthetic data set, the average surface error reached mm. The method was built into preoperative planning software designated for the selection of the best-fitting fixation material.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN
978-303004746-7
ISSN
0302-9743
e-ISSN
neuvedeno
Number of pages
13
Pages from-to
207-219
Publisher name
Springer-Verlag
Place of publication
New York
Event location
Granada
Event date
Sep 20, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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