Enhanced Model Selection for motion segmentation

In this paper a novel rank estimation technique for trajectories motion segmentation within the Local Subspace Affinity (LSA) framework is presented. This technique, called Enhanced Model Selection (EMS), is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built by LSA. The results on synthetic and real data show that without any a priori knowledge, EMS automatically provides an accurate and robust rank estimation, improving the accuracy of the final motion segmentation

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

Mophological analysis of the human vasculature from medical imaging. Application to cerebral and coranary arteries

In this project, we have investigated new ways of modelling and analysis of human vasculature from Medical images. The research was divided in two main areas: cerebral vasculature analysis and coronary arteries modeling. Regarding cerebral vasculature analysis, we have studed cerebral aneurysms, internal carotid and the Circle of Willis (CoW). Aneurysms are abnormal vessel enlargements that can rupture causing important cerebral damages or death. The understanding of this pathology, together with its virtual treatment, and image diagnosis and prognosis, includes identification and detailed measurement of the aneurysms. In this context, we have proposed two automatic aneurysm isolation method, to separate the abnormal part of the vessel from the healthy part, to homogenize and speed-up the processing pipeline usually employed to study this pathology, [Cardenes2011TMI, arrabide2011MedPhys]. The results obtained from both methods have been also compared and validatied in [Cardenes2012MBEC]. A second important task here the analysis of the internal carotid [Bogunovic2011Media] and the automatic labelling of the CoW, Bogunovic2011MICCAI, Bogunovic2012TMI]. The second area of research covers the study of coronary arteries, specially coronary bifurcations because there is where the formation of atherosclerotic plaque is more common, and where the intervention is more challenging. Therefore, we proposed a novel modelling method from Computed Tomography Angiography (CTA) images, combined with Conventional Coronary Angiography (CCA), to obtain realistic vascular models of coronary bifurcations, presented in [Cardenes2011MICCAI], and fully validated including phantom experiments in [Cardene2013MedPhys]. The realistic models obtained from this method are being used to simulate stenting procedures, and to investigate the hemodynamic variables in coronary bifurcations in the works submitted in [Morlachi2012, Chiastra2012]. Additionally, another preliminary work has been done to reconstruct the coronary tree from rotational angiography, and published in [Cardenes2012ISBI].

Multi-scale label interaction to improve object detection and segmentation

The project aims at advancing the state of the art in the use of context information for classification of image and video data. The use of context in the classification of images has been showed of great importance to improve the performance of actual object recognition systems. In our project we proposed the concept of Multi-scale Feature Labels as a general and compact method to exploit the local and global context. The feature extraction from the discriminative probability or classification confidence label field is of great novelty. Moreover the use of a multi-scale representation of the feature labels lead to a compact and efficient description of the context. The goal of the project has been also to provide a general-purpose method and prove its suitability in different image/video analysis problem. The two-year project generated 5 journal publications (plus 2 under submission), 10 conference publications (plus 2 under submission) and one patent (plus 1 pending). Of these publications, a relevant number make use of the main result of this project to improve the results in detection and/or segmentation of objects.

Medicine and Science in a New Medical-surgical Context: The Royal College of Surgery of Barcelona (1760–1843)

Taking the Royal College of Barcelona (1760 -1843) as a case study this paper shows the development of modern surgery in Spain initiated by Bourbon Monarchy founding new kinds of institutions through their academic activities of spreading scientific knowledge. Antoni Gimbernat was the most famousinternationally recognised Spanish surgeon. He was trained as a surgeon at the Royal College of Surgery in Cadiz and was later appointed as professor of theAnatomy in the College of Barcelona. He then became Royal Surgeon of King Carlos IV and with that esteemed position in Madrid he worked resiliently to improve the quality of the Royal colleges in Spain. Learning human bodystructure by performing hands-on dissections in the anatomical theatre has become a fundamental element of modern medical education. Gimbernat favoured the study of natural sciences, the new chemistry of Lavoisier and experimental physics in the academic programs of surgery. According to the study of a very relevant set of documents preserved in the library, the so-called “juntas literarias”, among the main subjects debated in the clinical sessions was the concept of human beings and diseases in relation to the development of the new experimental sciences. These documents showed that chemistry andexperimental physics were considered crucial tools to understand the unexplained processes that occurred in the diseased and healthy human bodyand in a medico-surgical context. It is important to stress that through these manuscripts we can examine the role and the reception of the new sciences applied to healing arts.

Summarization of specialized discourse: the case of medical articles in Spanish

In this article, we present the current state of our work on a linguistically-motivated model for automatic summarization of medical articles in Spanish. The model takes into account the results of an empirical study which reveals that, on the one hand, domain-specific summarization criteria can often be derived from the summaries of domain specialists, and, on the other hand, adequate summarization strategies must be multidimensional, i.e., cover various types of linguistic clues. We take into account the textual, lexical, discursive, syntactic and communicative dimensions. This is novel in the field of summarization. The experiments carried out so far indicate that our model is suitable to provide high quality summarizations.

Are tax subsidies for private medical insurance self-financing? Evidence from a microsimulation model for outpatient and inpatient episodes

This paper analyses whether or not tax subsidies to private medicalinsurance are self-financing by means of a structural approach. Weconstruct a simulation routine based on a microeconometric discretechoice model that allows us to evaluate the impact of premium changeson the utilisation of outpatient and inpatient health care services. Wesimulate the 1999 Spanish tax reform that abolished the tax deductionfor expenditures on private health insurance using a representativesample of the Catalan population. Prior to this reform, foregone taxrevenue arising from deductions after the purchase of private insuranceamounted to 69.2 M. per year. In contrast, the elimination of thesubsidies to private policies is estimated to generate an extra costfor the public sector of about 8.9 M. per year.

Patentes, regulación de precios e innovación en la industria farmacéutica

The trade-off between property rights/price regulation and innovation depends on countrycharacteristics and drug industry specificities. Access to drugs and innovation can bereconciled by seven ways that, among others, include: public health strengthening in thecountries with the largest access problems (those among the poor with the weakestinstitutions); public and private aid to make attractive R&D on neglected diseases; pricediscrimination with market segmentation; to require patent owners to choose eitherprotection in the rich countries or protection in the poor countries (but not both).Regarding price regulation, after a review of theoretical arguments and empirical evidence,seven strategies to reconcile health and industrial considerations are outlined, including:mitigation of the medical profession dependence on the pharmaceutical industry; considerationof a drug as an input of a production process; split drug authorization from public fundingdecisions; establish an efficiency minimum for all health production inputs; and stop theEuropean R&D hemorrhagia.

A fully-automatic caudate nucleus segmentation of brain MRI: application in volumetric analysis of pediatric attention-deficit/hyperactivity disorder

Background Accurate automatic segmentation of the caudate nucleus in magnetic resonance images (MRI) of the brain is of great interest in the analysis of developmental disorders. Segmentation methods based on a single atlas or on multiple atlases have been shown to suitably localize caudate structure. However, the atlas prior information may not represent the structure of interest correctly. It may therefore be useful to introduce a more flexible technique for accurate segmentations. Method We present Cau-dateCut: a new fully-automatic method of segmenting the caudate nucleus in MRI. CaudateCut combines an atlas-based segmentation strategy with the Graph Cut energy-minimization framework. We adapt the Graph Cut model to make it suitable for segmenting small, low-contrast structures, such as the caudate nucleus, by defining new energy function data and boundary potentials. In particular, we exploit information concerning the intensity and geometry, and we add supervised energies based on contextual brain structures. Furthermore, we reinforce boundary detection using a new multi-scale edgeness measure. Results We apply the novel CaudateCut method to the segmentation of the caudate nucleus to a new set of 39 pediatric attention-deficit/hyperactivity disorder (ADHD) patients and 40 control children, as well as to a public database of 18 subjects. We evaluate the quality of the segmentation using several volumetric and voxel by voxel measures. Our results show improved performance in terms of segmentation compared to state-of-the-art approaches, obtaining a mean overlap of 80.75%. Moreover, we present a quantitative volumetric analysis of caudate abnormalities in pediatric ADHD, the results of which show strong correlation with expert manual analysis. Conclusion CaudateCut generates segmentation results that are comparable to gold-standard segmentations and which are reliable in the analysis of differentiating neuroanatomical abnormalities between healthy controls and pediatric ADHD.

Advances in medical imaging applied to bone metastases

Bone metastases are the result of a primary cancer invasion which spreads into the bone marrow through the lymphogenous or hematogenous pathways. Bone metastases are a common complication of cancer.The primary cancers that most frequently metastasize to bone are breast and prostate cancer (65 - 75 %) amongst many others (thyroid 42 %, lung 36 % or kidney 35 %) (Suva et al., 2011). Although the exact incidence of bone metastases is unknown given its dependence on the type of primary cancer, it is estimated that 350,000 people die of bone metastases annually in the United States.

Spanish E-Consumer Segmentation and Positioning in Virtual Supermarkets Sector

This article analyses different factors that influence the purchasing behaviour of online supermarket customers. These factors are related to both the appearance of the website as well as the processes that take place when making the purchase. Based on these analyses, the various groups of consumers with homogenous behaviour are studied and positioned according to their attitudes. The analysis also allows the quality of the service offered by this kind of establishment to be defined, as well as the main dimensions in which it develops. In the conclusions, factors which should influence the manager of an online supermarket to improve the quality of its service are given

Reversible and high capacity data hiding in medical images

In this paper we introduce a highly efficient reversible data hiding system. It is based on dividing the image into tiles and shifting the histograms of each image tile between its minimum and maximum frequency. Data are then inserted at the pixel level with the largest frequency to maximize data hiding capacity. It exploits the special properties of medical images, where the histogram of their nonoverlapping image tiles mostly peak around some gray values and the rest of the spectrum is mainlyempty. The zeros (or minima) and peaks (maxima) of the histograms of the image tiles are then relocated to embed the data. The grey values of some pixels are therefore modified.High capacity, high fidelity, reversibility and multiple data insertions are the key requirements of data hiding in medical images. We show how histograms of image tiles of medical images can be exploited to achieve these requirements. Compared with data hiding method applied to the whole image, our scheme can result in 30%-200% capacity improvement and still with better image quality, depending on the medical image content. Additional advantages of the proposed method include hiding data in the regions of non-interest and better exploitation of spatial masking.

A segmentation analysis and segments profile of budget air travelers

Many Spanish destinations are now considering low cost airlines (LCA) important for attracting tourists. However, there is little evidence on the characteristics travelers using low cost airlines and their flight preferences. Typical segmentation of air travelers are business versus leisure travelers and business versus tourist fares. The aim of this paper is to obtain a deeper understanding of the demand of LCA through a segmentation analysis, based on 808 foreign travelers who used Girona airport, that focuses on low cost travelers’ valuations of different flight attributes and trip related characteristics

Automated monitoring of medical protocols: a secure and distributed architecture

The control of the right application of medical protocols is a key issue in hospital environments. For the automated monitoring of medical protocols, we need a domain-independent language for their representation and a fully, or semi, autonomous system that understands the protocols and supervises their application. In this paper we describe a specification language and a multi-agent system architecture for monitoring medical protocols. We model medical services in hospital environments as specialized domain agents and interpret a medical protocol as a negotiation process between agents. A medical service can be involved in multiple medical protocols, and so specialized domain agents are independent of negotiation processes and autonomous system agents perform monitoring tasks. We present the detailed architecture of the system agents and of an important domain agent, the database broker agent, that is responsible of obtaining relevant information about the clinical history of patients. We also describe how we tackle the problems of privacy, integrity and authentication during the process of exchanging information between agents.

Diagonal ear lobe crease and atherosclerosis: a review of the medical literature and dental implications

In Spain a significant number of individuals die from atherosclerotic disease of the coronary and carotid arteries without having classic risk factors and prodromal symptoms. The diagonal ear lobe crease (DELC) has been characterized in the medical literature as a surrogate marker which can identify high risk patients having occult atherosclerosis. This topic however has not been examined in either the medical or dental literature emanating from Spain. The majority of clinical, angiography and postmortem reports support the premise that DELC is a valuable extravascular physical sign able to distinguish some patients at risk of succumbing to atherosclerosis of the coronary arteries. A minority of studies have however failed to support this hypothesis. More recently reports using B mode ultrasound have also linked DELC to atherosclerosis of the carotid artery and another report has related DELC to the presence of calcified carotid artery atheromas on panoramic radiographs. DELC is readily visible during head and neck cancer screening examinations. In conjunction with the patient"s medical history, vital signs, and panoramic radiograph, the DELC may assist in atherosclerotic risk assessment