GridNet with automatic shape prior registration for automatic MRI cardiac segmentation

In this paper, we propose a fully automatic MRI cardiac segmentation method based on a novel deep convolutional neural network (CNN) designed for the 2017 ACDC MICCAI challenge. The novelty of our network comes with its embedded shape prior and its loss function tailored to the cardiac anatomy. Our model includes a cardiac centerof-mass regression module which allows for an automatic shape prior registration. Also, since our method processes raw MR images without any manual preprocessing and/or image cropping, our CNN learns both high-level features (useful to distinguish the heart from other organs with a similar shape) and low-level features (useful to get accurate segmentation results). Those features are learned with a multi-resolution conv-deconv "grid" architecture which can be seen as an extension of the U-Net. Experimental results reveal that our method can segment the left and right ventricles as well as the myocardium from a 3D MRI cardiac volume in 0.4 second with an average Dice coefficient of 0.90 and an average Hausdorff distance of 10.4 mm.Comment: 8 pages, 1 tables, 2 figure

Imagerie TEP au 18F-FDG du cancer du sein : étude du comportement métabolique des différents phénotypes tumoraux et prédiction de la réponse tumorale à la chimiothérapie néoadjuvante

Positron Emission Tomography (PET) with 18Fluoro-deoxyglucose (18F-FDG) is the reference imaging examination for in-vivo quantification of the glucidic metabolism of tumour cells. It allows for the monitoring of tumour metabolic changes during chemotherapy. Breast cancer comprises several distinct genomic entities with different biological characteristics and clinical behaviours, leading to different tailored treatments. The aim of this doctoral thesis was to evaluate the relationship between the different biological entities of breast cancer and the tumour metabolic behaviour during neoadjuvant chemotherapy. We have also retrieved, among the various metabolic parameters on PET images, the most reliable ones to predict, as early as after the first neoadjuvant cycle, the final tumour histologic response and patient’s outcome. We have also evaluated early changes in tumour blood flow, using a tumour first-pass model derived from an dynamic 18F-FDG-PET acquisition.The first article presented in this thesis has underlined the strong correlation between breast cancer subtypes, and the tumour metabolic behaviour during chemotherapy. The following three articles have demonstrated that tumour metabolic changes after the first neoadjuvant cycle can predict the final histologic complete response at the end of the treatment, both in triple-negative and HER2 positive tumours. Concerning the luminal/HER2 subtype, the early metabolic response mainly predicts patient’s outcome.These results should lead, in the near future, to PET-guided neoadjuvant strategies, in order to adapt the neoadjuvant treatment in poor-responding women. Such a strategy should lead to enhanced personalized medicine.La Tomographie par Emission de Positons (TEP) au 18Fluoro-désoxyglucose (18F-FDG) est l’imagerie de référence pour la quantification in vivo du métabolisme glucidique des cellules tumorales. Elle permet, entre autre, de suivre les modifications du métabolisme tumoral en cours de chimiothérapie. Le cancer du sein regroupe différentes entités génomiques dont les comportements clinico-biologiques et la prise en charge thérapeutique divergent. L’objectif de cette thèse était d’étudier le lien entre ces diverses entités biologiques du cancer du sein et le comportement métabolique tumoral en cours de chimiothérapie néoadjuvante. Nous avons également extrait, parmi les différents paramètres métaboliques tumoraux des images TEP, les critères les plus robustes pour prédire dès la fin dès la première cure de chimiothérapie néoadjuvante la réponse histologique finale et la survie des patientes. Nous avons également appliqué un modèle de mesure de la perfusion tumorale, dérivée d’une acquisition dynamique du premier passage artériel et tumoral du 18F-FDG.Le premier article de cette thèse souligne l’impact majeur du phénotype tumoral sur le comportement métabolique en cours de chimiothérapie de la tumeur primitive mammaire. Les trois articles suivants montrent que, pour les tumeurs triple-négatives et HER2 positives, les modifications métaboliques tumorales observées par la TEP au 18F-FDG prédisent la réponse histologique complète à l’issue du traitement. Concernant le phénotype tumoral luminal/HER2 négatif, la réponse métabolique apporte surtout une information pronostique. L’imagerie TEP au 18F-FDG pourrait permettre dans un avenir proche de guider les choix thérapeutiques du clinicien, en proposant une alternative thérapeutique aux patientes non-répondeuses identifiées dès la première cure de chimiothérapie néoadjuvante

A phenomenological model for predicting the effect of damping on wave turbulence spectra in vibrating plates

International audienceThin plates vibrating at large amplitudes may exhibit a strongly nonlinear regime that has to be studied within the framework of wave turbulence. Experimental studies have revealed the importance of the damping on the spectra of wave turbulence , which precludes for a direct comparison with the theoretical results, that assumes a Hamiltonian dynamics. A phenomenological model is here introduced so as to predict the effect of the damping on the turbulence spectra. Self-similar solutions are found and the cutoff frequency is expressed as function of the damping rate and the injected power

Privacy Preserving Image Registration

Image registration is a key task in medical imaging applications, allowing to represent medical images in a common spatial reference frame. Current literature on image registration is generally based on the assumption that images are usually accessible to the researcher, from which the spatial transformation is subsequently estimated. This common assumption may not be met in current practical applications, since the sensitive nature of medical images may ultimately require their analysis under privacy constraints, preventing to share the image content in clear form. In this work, we formulate the problem of image registration under a privacy preserving regime, where images are assumed to be confidential and cannot be disclosed in clear. We derive our privacy preserving image registration framework by extending classical registration paradigms to account for advanced cryptographic tools, such as secure multi-party computation and homomorphic encryption, that enable the execution of operations without leaking the underlying data. To overcome the problem of performance and scalability of cryptographic tools in high dimensions, we first propose to optimize the underlying image registration operations using gradient approximations. We further revisit the use of homomorphic encryption and use a packing method to allow the encryption and multiplication of large matrices more efficiently. We demonstrate our privacy preserving framework in linear and non-linear registration problems, evaluating its accuracy and scalability with respect to standard image registration. Our results show that privacy preserving image registration is feasible and can be adopted in sensitive medical imaging applications

Life cycle assessment of two baby food packaging alternatives: glass jars vs. plastic pots

Background, aim, and scope: This paper compares the life cycle assessment (LCA) of two packaging alternatives used for baby food produced by Nestlé: plastic pot and glass jar. The study considers the environmental impacts associated with packaging systems used to provide one baby food meal in France, Spain, and Germany in 2007. In addition, alternate logistical scenarios are considered which are independent of the two packaging options. The 200-g packaging size is selected as the basis for this study. Two other packaging sizes are assessed in the sensitivity analysis. Because results are intended to be disclosed to the public, this study underwent a critical review by an external panel of LCA experts. Materials and methods: The LCA is performed in accordance to the international standards ISO 14040 and ISO 14044. The packaging systems include the packaging production, the product assembly, the preservation process, the distribution, and the packaging end-of-life. The production of the content (before preservation process), as well as the use phase are not taken into account as they are considered not to change when changing packaging. The inventory is based on data obtained from the baby food producer and the suppliers, data from the scientific literature, and data from the ecoinvent database. Special care is taken to implement a system expansion approach for end-of-life open and closed loop recycling and energy production (ISO 14044). A comprehensive impact assessment is performed using two life cycle impact assessment methodologies: IMPACT 2002+ and CML 2001. An extensive uncertainty analysis using Monte Carlo as well as an extensive sensitivity study are performed on the inventory and the reference flows, respectively. Results: When looking at the impacts due to preservation process and packaging (considering identical distribution distances), we observe a small but significant environmental benefit of the plastic pot system over the glass jar system. Depending on the country, the impact is reduced by 14% to 27% for primary energy, 28% to 31% for global warming, 31% to 34% for respiratory inorganics, and 28% to 31% for terrestrial acidification/nutrification. The environmental benefit associated with the change in packaging mainly results from (a) production of plastic pot (including its end-of-life; 43% to 51% of total benefit), (b) lighter weight of packaging positively impacting transportation (20% to 35% of total benefit), and (c) new preservation process permitted by the plastic system (23% to 34% of total benefit). The jar or pot (including cap or lid, cluster, stretch film, and label) represents approximately half of the life cycle impacts, the logistics approximately one fourth, and the rest (especially on-site energy, tray, and hood) one fourth. Discussion: The sensitivity analysis shows that assumptions made in the basic scenarios are rather conservative for plastic pots and that the conclusions for the 200-g packaging size also apply to other packaging sizes. The uncertainty analysis performed on the inventory for the German market situation shows that the plastic pot system has less impact than the glass jar system while considering similar distribution distances with a confidence level above 97% for most impact categories. There is opportunity for further improvement independent of the type of packaging used, such as by reducing distribution distances while still optimizing lot size. The validity of the main conclusions presented in this study is confirmed by results of both impact assessment methodologies IMPACT 2002+ and CML 2001. Conclusions: For identical transportation distances, the plastic pot system shows a small but significant reduction in environmental burden compared to the glass jar system. Recommendations and perspectives: As food distribution plays an important role in the overall life cycle burdens and may vary between scenarios, it is important to avoid additional transportation of the packaged food in order to maintain or even improve the advantage of the plastic pot system. The present study focuses on the comparison of packaging systems and directly related consequences. It is recommended that further environmental optimization of the product also includes food manufacturing (before preservation process) and the supply chain of raw material

Are labels informative in semi-supervised learning? -- Estimating and leveraging the missing-data mechanism

Semi-supervised learning is a powerful technique for leveraging unlabeled data to improve machine learning models, but it can be affected by the presence of ``informative'' labels, which occur when some classes are more likely to be labeled than others. In the missing data literature, such labels are called missing not at random. In this paper, we propose a novel approach to address this issue by estimating the missing-data mechanism and using inverse propensity weighting to debias any SSL algorithm, including those using data augmentation. We also propose a likelihood ratio test to assess whether or not labels are indeed informative. Finally, we demonstrate the performance of the proposed methods on different datasets, in particular on two medical datasets for which we design pseudo-realistic missing data scenarios

Wave turbulence in vibrating plates

International audienceTurbulence is a general term used for describing the erratic motions displayed by nonlinearsystems that are driven far from their equilibrium position and thus display complicatedmotions involving different time and length scales. Wave turbulence (WT) share many common ideas with turbulence, in particular asbeing a statistical theory for out-of-equilibrium systems. A main difference resides in thefact that the persistence of waves is assumed.The application of WT to vibrating plates started with the theoretical derivation ofthe kinetic equation from the dynamical von Karman equations thatdescribe large-amplitude motions of thin plates. Since this date, numerous papershave been published covering experimental, theoretical and numerical materials. In fact,it appears that the vibrating plate is a perfect candidate for a thorough comparison ofexperiments with theoretical predictions. As compared to other physical systems such ascapillary or gravity waves for example, an experimental set-up with a fine control of energyinjection and a confortable range of wavelength is not too difficult to put in place. Secondly,the available measurement techniques allow one to get a complete and precise picture of thedynamics through the scales, both in the space and frequency domains. Finally, numericalcodes with good accuracy have been developed so that all the underlying assumptions ofthe theory as well as its predictions have been tested, both on the experimental and thenumerical levels

IMPACT 2002+: A new life cycle impact assessment methodology

The new IMPACT 2002+ life cycle impact assessment methodology proposes a feasible implementation of a combined midpoint/damage approach, linking all types of life cycle inventory results (elementary flows and other interventions) via 14 midpoint categories to four damage categories. For IMPACT 2002+, new concepts and methods have been developed, especially for the comparative assessment of human toxicity and ecotoxicity. Human Damage Factors are calculated for carcinogens and non-carcinogens, employing intake fractions, best estimates of dose-response slope factors, as well as severities. The transfer of contaminants into the human food is no more based on consumption surveys, but accounts for agricultural and livestock production levels. Indoor and outdoor air emissions can be compared and the intermittent character of rainfall is considered. Both human toxicity and ecotoxicity effect factors are based on mean responses rather than on conservative assumptions. Other midpoint categories are adapted from existing characterizing methods (Eco-indicator 99 and CML 2002). All midpoint scores are expressed in units of a reference substance and related to the four damage categories human health, ecosystem quality, climate change, and resources. Normalization can be performed either at midpoint or at damage level. The IMPACT 2002+ method presently provides characterization factors for almost 1500 different LCI-results, which can be downloaded at http://www.epfl.ch/impac

Privacy Preserving Image Registration

International audienceImage registration is a key task in medical imaging applications, allowing to represent medical images in a common spatial reference frame. Current literature on image registration is generally based on the assumption that images are usually accessible to the researcher, from which the spatial transformation is subsequently estimated. This common assumption may not be met in current practical applications, since the sensitive nature of medical images may ultimately require their analysis under privacy constraints, preventing to share the image content in clear form. In this work, we formulate the problem of image registration under a privacy preserving regime, where images are assumed to be confidential and cannot be disclosed in clear. We derive our privacy preserving image registration framework by extending classical registration paradigms to account for advanced cryptographic tools, such as secure multi-party computation and homomorphic encryption, that enable the execution of operations without leaking the underlying data. To overcome the problem of performance and scalability of cryptographic tools in high dimensions, we first propose to optimize the underlying image registration operations using gradient approximations. We further revisit the use of homomorphic encryption and use a packing method to allow the encryption and multiplication of large matrices more efficiently. We demonstrate our privacy preserving framework in linear and nonlinear registration problems, evaluating its accuracy and scalability with respect to standard image registration. Our results show that privacy preserving image registration is feasible and can be adopted in sensitive medical imaging applications