1 resultado para Non-uniform flow
em CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal
Filtro por publicador
- ABACUS. Repositorio de Producción Científica - Universidad Europea (1)
- Aberdeen University (4)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (15)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (15)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (5)
- Archimer: Archive de l'Institut francais de recherche pour l'exploitation de la mer (1)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (1)
- Aston University Research Archive (47)
- Biblioteca de Teses e Dissertações da USP (1)
- Biblioteca Digital | Sistema Integrado de Documentación | UNCuyo - UNCUYO. UNIVERSIDAD NACIONAL DE CUYO. (1)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (12)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (118)
- Bioline International (1)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (38)
- Brock University, Canada (3)
- Bucknell University Digital Commons - Pensilvania - USA (4)
- Bulgarian Digital Mathematics Library at IMI-BAS (6)
- CaltechTHESIS (1)
- CentAUR: Central Archive University of Reading - UK (81)
- CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal (1)
- Cochin University of Science & Technology (CUSAT), India (1)
- Coffee Science - Universidade Federal de Lavras (2)
- Collection Of Biostatistics Research Archive (1)
- Consorci de Serveis Universitaris de Catalunya (CSUC), Spain (19)
- CORA - Cork Open Research Archive - University College Cork - Ireland (2)
- Dalarna University College Electronic Archive (2)
- Department of Computer Science E-Repository - King's College London, Strand, London (1)
- Digital Commons - Michigan Tech (17)
- Digital Commons at Florida International University (24)
- Digital Peer Publishing (1)
- DigitalCommons - The University of Maine Research (1)
- DigitalCommons@The Texas Medical Center (5)
- DigitalCommons@University of Nebraska - Lincoln (2)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (24)
- DRUM (Digital Repository at the University of Maryland) (6)
- Duke University (3)
- FUNDAJ - Fundação Joaquim Nabuco (1)
- Glasgow Theses Service (3)
- Illinois Digital Environment for Access to Learning and Scholarship Repository (3)
- Instituto de Engenharia Nuclear, Brazil - Carpe dIEN (1)
- Instituto Politécnico do Porto, Portugal (9)
- Iowa Publications Online (IPO) - State Library, State of Iowa (Iowa), United States (6)
- Lume - Repositório Digital da Universidade Federal do Rio Grande do Sul (1)
- Martin Luther Universitat Halle Wittenberg, Germany (1)
- Massachusetts Institute of Technology (4)
- Memorial University Research Repository (1)
- National Center for Biotechnology Information - NCBI (1)
- Nottingham eTheses (3)
- Publishing Network for Geoscientific & Environmental Data (29)
- QSpace: Queen's University - Canada (3)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (7)
- Repositório Científico da Universidade de Évora - Portugal (1)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (7)
- Repositório da Escola Nacional de Administração Pública (ENAP) (1)
- Repositório da Produção Científica e Intelectual da Unicamp (29)
- Repositório da Universidade Federal do Espírito Santo (UFES), Brazil (1)
- Repositório Digital da UNIVERSIDADE DA MADEIRA - Portugal (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (1)
- Repositório Institucional da Universidade de Brasília (2)
- Repositório Institucional da Universidade Federal do Rio Grande - FURG (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (108)
- Repositorio Institucional Universidad de Medellín (1)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (4)
- SAPIENTIA - Universidade do Algarve - Portugal (1)
- Savoirs UdeS : plateforme de diffusion de la production intellectuelle de l’Université de Sherbrooke - Canada (2)
- Scielo Saúde Pública - SP (24)
- Universidad de Alicante (3)
- Universidad del Rosario, Colombia (1)
- Universidad Politécnica de Madrid (62)
- Universidade Complutense de Madrid (2)
- Universidade de Lisboa - Repositório Aberto (1)
- Universidade do Minho (3)
- Universidade Federal do Pará (3)
- Universidade Federal do Rio Grande do Norte (UFRN) (3)
- Universita di Parma (1)
- Universitat de Girona, Spain (3)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (7)
- Université de Lausanne, Switzerland (41)
- Université de Montréal (2)
- Université de Montréal, Canada (12)
- Université Laval Mémoires et thèses électroniques (1)
- University of Michigan (9)
- University of Queensland eSpace - Australia (51)
- University of Washington (1)
- WestminsterResearch - UK (1)
- Worcester Research and Publications - Worcester Research and Publications - UK (1)
Resumo:
In daily cardiology practice, assessment of left ventricular (LV) global function using non-invasive imaging remains central for the diagnosis and follow-up of patients with cardiovascular diseases. Despite the different methodologies currently accessible for LV segmentation in cardiac magnetic resonance (CMR) images, a fast and complete LV delineation is still limitedly available for routine use. In this study, a localized anatomically constrained affine optical flow method is proposed for fast and automatic LV tracking throughout the full cardiac cycle in short-axis CMR images. Starting from an automatically delineated LV in the end-diastolic frame, the endocardial and epicardial boundaries are propagated by estimating the motion between adjacent cardiac phases using optical flow. In order to reduce the computational burden, the motion is only estimated in an anatomical region of interest around the tracked boundaries and subsequently integrated into a local affine motion model. Such localized estimation enables to capture complex motion patterns, while still being spatially consistent. The method was validated on 45 CMR datasets taken from the 2009 MICCAI LV segmentation challenge. The proposed approach proved to be robust and efficient, with an average distance error of 2.1 mm and a correlation with reference ejection fraction of 0.98 (1.9 ± 4.5%). Moreover, it showed to be fast, taking 5 seconds for the tracking of a full 4D dataset (30 ms per image). Overall, a novel fast, robust and accurate LV tracking methodology was proposed, enabling accurate assessment of relevant global function cardiac indices, such as volumes and ejection fraction.