Left-ventricular epi- and endocardium extraction from 3D ultrasound images using an automatically constructed 3D ASM

© 2014 Taylor & Francis.In this paper, we propose an automatic method for constructing an active shape model (ASM) to segment the complete cardiac left ventricle in 3D ultrasound (3DUS) images, which avoids costly manual landmarking. The automatic construction of the ASM has already been addressed in the literature; however, the direct application of these methods to 3DUS is hampered by a high level of noise and artefacts. Therefore, we propose to construct the ASM by fusing the multidetector computed tomography data, to learn the shape, with the artificially generated 3DUS, in order to learn the neighbourhood of the boundaries. Our artificial images were generated by two approaches: a faster one that does not take into account the geometry of the transducer, and a more comprehensive one, implemented in Field II toolbox. The segmentation accuracy of our ASM was evaluated on 20 patients with left-ventricular asynchrony, demonstrating plausibility of the approach

Look-alike humans identified by facial recognition algorithms show genetic similarities

We thank François Brunelle for providing the look-alike images. We thank CERCA Programme/Generalitat de Catalunya and the Josep Carreras Foundation for institutional support. This work was funded by the governments of Catalonia (2017SGR1080) and Spain (RTI2018-094049-B-I00, SAF2014-55000, and TIN2017-90124-P) and the Cellex Foundation. M.E. conceived and designed the study; R.S.J. M.R. C.A.G.-P. M.C.d.M. D.P. S.M. V.D. P.C. M.F.-B. I.O. C.L.-F. A.N. C.F.-T. D.A. F.M.S. X.B. A.V. and M.E. analyzed multiomics and questionnaire data; R.J. and M.E. wrote the manuscript with contributions and approval from all authors. M.E. is a consultant of Ferrer International and Quimatryx. S.M. is an employee of Ferrer International. C.F.-T. is chief technical officer of Herta Security.We thank François Brunelle for providing the look-alike images. We thank CERCA Programme/Generalitat de Catalunya and the Josep Carreras Foundation for institutional support. This work was funded by the governments of Catalonia (2017SGR1080) and Spain (RTI2018-094049-B-I00, SAF2014-55000, and TIN2017-90124-P) and the Cellex Foundation.The human face is one of the most visible features of our unique identity as individuals. Interestingly, monozygotic twins share almost identical facial traits and the same DNA sequence but could exhibit differences in other biometrical parameters. The expansion of the world wide web and the possibility to exchange pictures of humans across the planet has increased the number of people identified online as virtual twins or doubles that are not family related. Herein, we have characterized in detail a set of "look-alike" humans, defined by facial recognition algorithms, for their multiomics landscape. We report that these individuals share similar genotypes and differ in their DNA methylation and microbiome landscape. These results not only provide insights about the genetics that determine our face but also might have implications for the establishment of other human anthropometric properties and even personality characteristics

A Benchmark for Geometric Facial Beauty Study

2nd International Conference on Medical Biometrics, ICMB 2010, Hong Kong, 28-30 June 2010This paper presents statistical analyses for facial beauty study. A large-scale database was built, containing 23412 frontal face images, 875 of them are marked as beautiful. We focus on the geometric feature defined by a set of landmarks on faces. A normalization approach is proposed to filter out the non-shape variations - translation, rotation, and scale. The normalized features are then mapped to its tangent space, in which we conduct statistical analyses: Hotelling's T2 test is applied for testing whether female and male mean faces have significant difference; Principal Component Analysis (PCA) is applied to summarize the main modes of shape variation and do dimension reduction; A criterion based on the Kullback-Leibler (KL) divergence is proposed to evaluate different hypotheses and models. The KL divergence measures the distribution difference between the beautiful group and the whole population. The results show that male and female faces come from different Gaussian distributions, but the two distributions overlap each other severely. By measuring the KL divergence, it shows that multivariate Gaussian model embodies much more beauty related information than the averageness hypothesis and the symmetry hypothesis. We hope the large-scale database and the proposed evaluation methods can serve as a benchmark for further studies.Department of Computin