Abstract
Breast cancer is one of the most mediated malignant diseases, because of its high incidence and prevalence, but principally due to its physical and psychological invasiveness. Surgeons and patients have often many options to consider for undergoing the procedure. The ability to visualise the potential outcomes of the surgery and make decisions on their surgical options is, therefore, very important for patients and surgeons. In this paper we investigate the fitting of a 3d point cloud of the breast to a parametric model usable in surgery planning, obtaining very promising results with real data.

Abstract
In classification, when there is a disproportion in the number of observations in each class, the data is said to be class imbalance. Class imbalance is pervasive in real world applications of data classification and has been the focus of much research. The minority class contributes too little to the decision boundary because the learning process learns from each observation in isolation. In this paper, we discuss the application of learning pairwise rankers as a solution to class imbalance. We compare ranking models to alternatives from the literature.

Abstract
Breast Cancer is still a serious health threat to women, both physically and psychologically. Fortunately, treatments involving complete breast removal are rarely needed today, as better treatment options are available. Mammography can show changes in the breast up to two years before a physician can feel them. Computer-aided detection and diagnosis is considered to be one of the most promising approaches that may improve the efficiency of mammography. Furthermore, there is a strong correlation between the presence of calcifications and the occurrence of breast cancer. In this paper we present a new technique to detect calcifications in mammogram images. The main objective is to support radiologists with automatic detection methods applied to medical images. Motivated by the fact that calcifications, when compared to the rest of the image, exhibit irregular characteristics, a technique based on Bayesian surprise is used. Tests were performed using INBreast, a recent fully annotated database, composed of full field digital mammograms. Comparison both with a recently proposed state of the art method and other common image techniques showed the superiority of our method. False positives are, however, still an issue and further studies focused on their reduction while maintaining a high sensitivity are planned.

Abstract
Automatic vision systems are widely used in sports competition to analyze individual and collective performance during the matches. However, the complex implementation based on multiple fixed cameras and the human intervention on the process makes this kind of systems expensive and not suitable for the big majority of the teams. In this paper we propose a low-cost, portable and flexible solution based on the use of Unmanned Air Vehicles to capture images from indoor soccer games. Since these vehicles suffer from vibrations and disturbances, the acquired video is very unstable, presenting a set of unusual problems in this type of applications. We propose a complete video-processing framework, including video stabilization, camera calibration, player detection, and team performance analysis. The results showed that camera calibration was able to correct automatically image-to-world homography; the player detection precision and recall was around 75%; and the high-level data interpretation showed a strong similarity with ground-truth derived results.

Abstract
Breast-conserving approaches aim to attain better aesthetic results in addition to local control and achieving survival rates equivalent to mastectomy in patients with breast cancer. While the oncologic outcome of breast conservation procedures is easily estimated objectively by disease-free and overall survival rates, the cosmetic outcome has no standard of evaluation. Although breast conservation techniques have been widely studied, different forms of evaluation and heterogeneous working practices have contributed to different aesthetic results. As this scenario suggests, the evaluation of aesthetic results should be mandatory in any institution performing breast cancer treatment, contributing to the improvement of current strategies by enabling the identification of variables which have a significant impact on the final aesthetic result. In the process of assessing cosmetic outcomes there are several important issues that should be considered: which factors have a crucial impact on the cosmetic outcome of Breast Cancer Conservation Treatment (BCCT); which parameters or features should be evaluated in the cosmetic assessment of BCCT; how patients are evaluated; which scales are used in this evaluation; which methods and technological solutions are available for the evaluation of cosmetic results of BCCT. In this paper we try to discuss all these questions, with an emphasis on the objective methods and corresponding technologies used in the aesthetic evaluation of BCCT. The most relevant publications related to the mentioned topics are presented, critically analysed and put in chronological perspective. Current and future trends are also discussed.

Abstract
Biometric systems based on iris are vulnerable to several attacks, particularly direct attacks consisting on the presentation of a fake iris to the sensor. The development of iris liveness detection techniques is crucial for the deployment of iris biometric applications in daily life specially in the mobile biometric field. The 1st Mobile Iris Liveness Detection Competition (MobILive) was organized in the context of IJCB2014 in order to record recent advances in iris liveness detection. The goal for (MobILive) was to contribute to the state of the art of this particular subject. This competition covered the most common and simple spoofing attack in which printed images from an authorized user are presented to the sensor by a non-authorized user in order to obtain access. The benchmark dataset was the MobBIOfake database which is composed by a set of 800 iris images and its corresponding fake copies (obtained from printed images of the original ones captured with the same handheld device and in similar conditions). In this paper we present a brief description of the methods and the results achieved by the six participants in the competition. © 2014 IEEE.