Virtual 2D-3D Fracture Reduction with Bone Length Recovery Using Statistical Shape Models

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/00216224:14310/18:00106612 RIV/00216305:26230/18:PU130775 RIV/00843989:_____/18:E0107978

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Virtual 2D-3D Fracture Reduction with Bone Length Recovery Using Statistical Shape Models

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Virtual 2D-3D Fracture Reduction with Bone Length Recovery Using Statistical Shape Models

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

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

Počet stran výsledku

13

Strana od-do

207-219

Název nakladatele

Springer-Verlag

Místo vydání

New York

Místo konání akce

Granada

Datum konání akce

20. 9. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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