The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the preoperative tumor volume is essential. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming process that can be overcome with the help of computerized segmentation methods. In this contribution, two methods for World Health Organization (WHO) grade IV glioma segmentation in the human brain are compared using magnetic resonance imaging (MRI) patient data from the clinical routine. One method uses balloon inflation forces, and relies on detection of high intensity tumor boundaries that are coupled with the use of contrast agent gadolinium. The other method sets up a directed and weighted graph and performs a min-cut for optimal segmentation results. The ground truth of the tumor boundaries - for evaluating the methods on 27 cases - is manually extracted by neurosurgeons with several years of experience in the resection of gliomas. A comparison is performed using the Dice Similarity Coefficient (DSC), a measure for the spatial overlap of different segmentation results.

Objective – The research was undertaken with the aim of establishing the range and frequency of congenital heart disease (CHD) in children with Down syndrome (DS), who are monitored at paediatric cardiology centres in Bosnia and Herzegovina, its association with other anomalies, the time of diagnosis of DS and CHD, and to analyse their surgical care.  Patients and methods – By a cross-sectional study, data was collected on children aged from 0 to 18 years with DS and CHD who were monitored at paediatric cardiology centres of primary, secondary and tertiary health care (Banja Luka, BihaA‡, Bijeljina, Mostar, Sarajevo, Tuzla and Zenica) in Bosnia and Herzegovina.  Results – Data for 100 children (51 boys and 49 girls) of an average age of 6.1 (from 0 to 17.1) were collected and analysed. The most frequently diagnosed CHD was atrioventricular septal defect, which was found in 36% of children followed by ventricular septal defect in 33%. In 79% children the CHD was isolated and 21% had multiple heart anomalies. Associated anomalies of other systems were found in 26% of children. In only one case was an intrauterine suspicion of DS established. A statistically significant reduction in the age of post-natal diagnosis of DS and CNHD was registered. In 73% patients cardiosurgical treatment was indicated, 43% underwent surgery, 19% are waiting for surgery and in 11% pulmonary hypertension developed.  Conclusion – The range of CHD found in children with DS in Bosnia and Herzegovina does not differ from most similar research. The results obtained show that in the period in question there was insufficient prenatal diagnostics of DS and CHD. Postnatal diagnostics, although also insufficient at the beginning of the period in question, significantly improved over time, which resulted in a reduction of the age at which the diagnosis of DS and CHD was established. Moreover there was a clear reduction in the time difference between the diagnosis of DS and the diagnosis of CHD. However, the possibilities of early cardio-surgical treatment are still limited. The results should serve in drawing up a plan of prospective monitoring of these patients in Bosnia and Herzegovina in order to define better their specific health needs.

Gliomas are the most common primary brain tumors, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the preoperative tumor volume is essential. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming process that can be overcome with the help of computer-assisted segmentation methods. In this paper, a semi-automatic approach for World Health Organization (WHO) grade IV glioma segmentation is introduced that uses balloon inflation forces, and relies on the detection of high-intensity tumor boundaries that are coupled by using contrast agent gadolinium. The presented method is evaluated on 27 magnetic resonance imaging (MRI) data sets and the ground truth data of the tumor boundaries - for evaluation of the results - are manually extracted by neurosurgeons.

We propose a general superstructure and a model for the global optimization for integrated process water networks. The superstructure consists of multiple sources of water, water-using processes, wastewater treatment, and pre-treatment operations. Unique features are that all feasible interconnections are considered between them and multiple sources of water can be used. The proposed model is formulated as a nonlinear programing (NLP) and as a mixed integer nonlinear programing (MINLP) problem for the case when 0–1 variables are included for the cost of piping and to establish optimal trade-offs between cost and network complexity. To effectively solve the NLP and MINLP models to global optimality we propose tight bounds on the variables, which are expressed as general equations. We also incorporate the cut proposed by Karuppiah and Grossmann to significantly improve the strength of the lower bound for the global optimum. The proposed model is tested on several examples. © 2010 American Institute of Chemical Engineers AIChE J, 2011