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
The use of images acquired in unconstrained scenarios is giving rise to new challenges in the field of iris recognition. Many works in literature reported excellent results in both iris segmentation and recognition but mostly with images acquired in controlled conditions. The intention to broaden the field of application of iris recognition, such as airport security or personal identification in mobile devices, is therefore hindered by the inherent unconstrained nature under which images are to be acquired. The proposed work focuses on mutual context information from iris centre and iris limbic and pupillary contours to perform robust and accurate iris segmentation in noisy images. The developed algorithm was tested on the MobBIO database with a promising 96% segmentation accuracy for the limbic contour.

Abstract
The detection of staff lines is the first step of most Optical Music Recognition (OMR) systems. Its great significance derives from the ease with which we can then proceed with the extraction of musical symbols. All OMR tasks are usually achieved using binary images by setting thresholds that can be local or global. These techniques however, may remove relevant information of the music sheet and introduce artifacts which will degrade results in the later stages of the process. It arises therefore a need to create a method that reduces the loss of information due to the binarization. The baseline for the methodology proposed in this paper follows the shortest path algorithm proposed in [1]. The concept of strong staff pixels (SSP's), which is a set of pixels with a high probability of belonging to a staff line, is proposed to guide the cost function. The SSP allows to overcome the results of the binary based detection and to generalize the binary framework to grayscale music scores. The proposed methodology achieves good results.

Abstract
Classification is one of the most important tasks of machine learning. Although the most well studied model is the two-class problem, in many scenarios there is the opportunity to label critical items for manual revision, instead of trying to automatically classify every item. In this paper we tailor a paradigm initially proposed for the classification of ordinal data to address the classification problem with reject option. The technique reduces the problem of classifying with reject option to the standard two-class problem. The introduced method is then mapped into support vector machines and neural networks. Finally, the framework is extended to multiclass ordinal data with reject option. An experimental study with synthetic and real datasets verifies the usefulness of the proposed approach.

Abstract

Abstract
The international randomised targeted intraoperative radiotherapy (TARGIT) trial has demonstrated evidence of non-inferiority between the novel technique of TARGIT (intra-operative radiotherapy with Intrabeam(A (R))) and conventional external beam radiotherapy (EBRT) in women with early breast cancer in terms of the primary outcome measure of risk of local relapse within the treated breast. Cosmesis is an increasingly important outcome of breast conserving treatment with both surgery and radiotherapy contributing to this. It was unknown if the single high dose of TARGIT may lead to damaging fibrosis and thus impair cosmesis further, so we objectively evaluated the aesthetic outcome of patients within the TARGIT randomised controlled trial. We have used an objective assessment tool for evaluation of cosmetic outcome. Frontal digital photographs were taken at baseline (before TARGIT or EBRT) and yearly thereafter for up to 5 years. The photographs were analysed by BCCT.core, a validated software which produces a composite score based on symmetry, colour and scar. 342 patients were assessed, median age at baseline 64 years (IQR 59-68). The scores were dichotomised into Excellent and Good (EG), and Fair and Poor (FP). There were statistically significant increases in the odds of having an outcome of EG for patients in the TARGIT group relative to the EBRT group at year 1 (OR 2.07, 95 % CI 1.12-3.85, p = 0.021) and year 2 (OR 2.11, 95 % CI 1.0-4.45, p = 0.05). Following a totally objective assessment in a randomised setting, the aesthetic outcome of patients demonstrates that those treated with TARGIT have a superior cosmetic result to those patients who received conventional external beam radiotherapy.