Automatic Liver Segmentation Using an Adversarial Image-to-Image Network

Automatic liver segmentation in 3D medical images is essential in many clinical applications, such as pathological diagnosis of hepatic diseases, surgical planning, and postoperative assessment. However, it is still a very challenging task due to the complex background, fuzzy boundary, and various appearance of liver. In this paper, we propose an automatic and efficient algorithm to segment liver from 3D CT volumes. A deep image-to-image network (DI2IN) is first deployed to generate the liver segmentation, employing a convolutional encoder-decoder architecture combined with multi-level feature concatenation and deep supervision. Then an adversarial network is utilized during training process to discriminate the output of DI2IN from ground truth, which further boosts the performance of DI2IN. The proposed method is trained on an annotated dataset of 1000 CT volumes with various different scanning protocols (e.g., contrast and non-contrast, various resolution and position) and large variations in populations (e.g., ages and pathology). Our approach outperforms the state-of-the-art solutions in terms of segmentation accuracy and computing efficiency.Comment: Accepted by MICCAI 201

3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes

While deep convolutional neural networks (CNN) have been successfully applied for 2D image analysis, it is still challenging to apply them to 3D anisotropic volumes, especially when the within-slice resolution is much higher than the between-slice resolution and when the amount of 3D volumes is relatively small. On one hand, direct learning of CNN with 3D convolution kernels suffers from the lack of data and likely ends up with poor generalization; insufficient GPU memory limits the model size or representational power. On the other hand, applying 2D CNN with generalizable features to 2D slices ignores between-slice information. Coupling 2D network with LSTM to further handle the between-slice information is not optimal due to the difficulty in LSTM learning. To overcome the above challenges, we propose a 3D Anisotropic Hybrid Network (AH-Net) that transfers convolutional features learned from 2D images to 3D anisotropic volumes. Such a transfer inherits the desired strong generalization capability for within-slice information while naturally exploiting between-slice information for more effective modelling. The focal loss is further utilized for more effective end-to-end learning. We experiment with the proposed 3D AH-Net on two different medical image analysis tasks, namely lesion detection from a Digital Breast Tomosynthesis volume, and liver and liver tumor segmentation from a Computed Tomography volume and obtain the state-of-the-art results

Cystic fibrosis mice carrying the missense mutation G551D replicate human genotype phenotype correlations

We have generated a mouse carrying the human G551D mutation in the cystic fibrosis transmembrane conductance regulator gene (CFTR) by a one-step gene targeting procedure. These mutant mice show cystic fibrosis pathology but have a reduced risk of fatal intestinal blockage compared with 'null' mutants, in keeping with the reduced incidence of meconium ileus in G551D patients. The G551D mutant mice show greatly reduced CFTR-related chloride transport, displaying activity intermediate between that of cftr(mlUNC) replacement ('null') and cftr(mlHGU) insertional (residual activity) mutants and equivalent to approximately 4% of wild-type CFTR activity. The long-term survival of these animals should provide an excellent model with which to study cystic fibrosis, and they illustrate the value of mouse models carrying relevant mutations for examining genotype-phenotype correlations

Exploring futures of food and farming systems: the Agrimonde scenarios

This brief series was developed in preparation for the Foresight Breakout Session of the Global Conference on Agricultural Research for Development (GCARD 2012) and the Global Foresight Hub1. The briefs were written to communicate to a wider audience, such as policy makers, civil society organizations, researchers, and funders. The briefs were classified into three categories: Future Studies, Regional Update, and Visioning. http://www.fao.org/docs/eims/upload/305838/Brief%2016.pd

Field-induced phase transitions in a Kondo insulator

We study the magnetic-field effect on a Kondo insulator by exploiting the periodic Anderson model with the Zeeman term. The analysis using dynamical mean field theory combined with quantum Monte Carlo simulations determines the detailed phase diagram at finite temperatures. At low temperatures, the magnetic field drives the Kondo insulator to a transverse antiferromagnetic phase, which further enters a polarized metallic phase at higher fields. The antiferromagnetic transition temperature $T_c$ takes a maximum when the Zeeman energy is nearly equal to the quasi-particle gap. In the paramagnetic phase above $T_c$, we find that the electron mass gets largest around the field where the quasi-particle gap is closed. It is also shown that the induced moment of conduction electrons changes its direction from antiparallel to parallel to the field.Comment: 7 pages, 6 figure

Flambée des prix alimentaires internationaux : opportunité ou désastre pour les populations les plus pauvres ?

This article suggests a conceptual framework for analyzing the consequences of the recent prices increase on the poorest people in the world. The complexity of mechanisms at work is demonstrated. At the global level, the analysis points out that Sub Saharan Africa exhibits the worst situation but a high diversity exists between nations. Three countries were chosen for an analysis of local markets and households impacts (Cameroon, Mali and Senegal). In Senegal prices transmission on local markets is important and negative impacts on poor households are observed. By contrast domestic prices exhibit very few changes in Mali. Cameroon exhibits an intermediate situation between these two cases. ...French Abstract : Cet article propose et applique un cadre d'analyse pour l'étude des conséquences de la flambée des prix des denrées alimentaires sur les populations pauvres des pays du Sud. Il met en évidence la complexité des mécanismes à l'oeuvre et la diversité des cas. Parmi les grands ensembles régionaux, l'Afrique Sub-saharienne apparaît particulièrement exposée à des impacts négatifs, mais les situations sont contrastées d'une nation à l'autre. Trois pays sont retenus pour une analyse au niveau des marchés locaux et des ménages (Cameroun, Mali, Sénégal). Au Sénégal, la contagion aux prix alimentaires intérieurs est la plus importante, elle a des conséquences négatives sur les ménages, en particulier les plus pauvres. Au Mali par contre, on note très peu d'impacts sur les marchés domestiques. Le Cameroun illustre une situation intermédiaire entre ces deux extrêmes.FOOD PRICES INCREASE; PRICES TRANSMISSION; FOOD TRADE; POVERTY; FLAMBEE DES PRIX ALIMENTAIRES; CONNEXION DES MARCHES NATIONAUX ET INTERNATIONAUX; COMMERCE ALIMENTAIRE; PAUVRETE

Multiplet Effects in the Quasiparticle Band Structure of the f1−f2f^1-f^2 Anderson Model

In this paper, we examine the mean field electronic structure of the $f^1-f^2$ Anderson lattice model in a slave boson approximation, which should be useful in understanding the physics of correlated metals with more than one f electron per site such as uranium-based heavy fermion superconductors. We find that the multiplet structure of the $f^2$ ion acts to quench the crystal field splitting in the quasiparticle electronic structure. This is consistent with experimental observations in such metals as $UPt_3$.Comment: 9 pages, revtex, 3 uuencoded postscript figures attached at en