Igen kis súlyú vagy 32. gesztációs hétnél éretlenebb koraszülöttek halálozási mutatói Magyarországon a EuroHOPE kutatás tükrében

INTRODUCTION: Care provision for very low birth weight and very low gestational age newborns requires high level clinical preparedness. Appropriate care and care management reduce mortality. AIM: To present Hungarian and international outcomes and local regional differences characterizing neonatal care in 2006-2008, based on the results of the EuroHOPE study. METHOD: Hungarian data were created by linking the obstetrics registry with the financing database of the Health Insurance Fund. Resulting from peculiarities of these databases and clinically justified exclusions, 3562 newborns were included. RESULTS: Hungarian risk-adjusted 365-day mortality rate was significantly higher than in most of the studied countries. Incidence of diseases correlated with higher mortality risk was highest in Hungary. Mortality in two Hungarian counties was worse than expected based on modelling, while it was better in one county. CONCLUSIONS: Systematic factors might cause these results. Relatively low usage rate of steroid prophylaxis in Hungary might contribute to unfavorable mortality figures. A common unique identifier would help database linkage. Orv. Hetil., 2016, 157(41), 1649-1656

Recovering refined surface normals for relighting clothing in dynamic scenes

In this paper we present a method to relight captured 3D video sequences of non-rigid, dynamic scenes, such as clothing of real actors, reconstructed from multiple view video. A view-dependent approach is introduced to refine an initial coarse surface reconstruction using shape-from-shading to estimate detailed surface normals. The prior surface approximation is used to constrain the simultaneous estimation of surface normals and scene illumination, under the assumption of Lambertian surface reflectance. This approach enables detailed surface normals of a moving non-rigid object to be estimated from a single image frame. Refined normal estimates from multiple views are integrated into a single surface normal map. This approach allows highly non-rigid surfaces, such as creases in clothing, to be relit whilst preserving the detailed dynamics observed in video

Relighting of Facial Images

Abstract We present a novel method to relight video sequences given known surface shape and illumination

Relightning of Facial Video

We present a novel method to relight video sequences given known surface shape and illumination. The method preserves fine visual details. It requires single view video frames, approximate 3D shape and standard studio illumination only, making it applicable in studio production. The technique is demonstrated for relighting video sequences of face

Relighting of Facial Video

We present a novel method to relight video sequences given known surface shape and illumination. The method preserves fine visual details. It requires single view video frames, approximate 3D shape and standard studio illumination only, making it applicable in studio production. The technique is demonstrated for relighting video sequences of face

Recovering Refined Surface Normals for Relighting Clothing in Dynamic Scenes

In this paper we present a method to relight captured 3D video sequences of non-rigid, dynamic scenes, such as clothing of real actors, reconstructed from multiple view video. A view-dependent approach is introduced to refine an initial coarse surface reconstruction using shape-from-shading to estimate detailed surface normals. The prior surface approximation is used to constrain the simultaneous estimation of surface normals and scene illumination, under the assumption of Lambertian surface reflectance. This approach enables detailed surface normals of a moving non-rigid object to be estimated from a single image frame. Refined normal estimates from multiple views are integrated into a single surface normal map. This approach allows highly non-rigid surfaces, such as creases in clothing, to be relit whilst preserving the detailed dynamics observed in video