3D Reconstruction of Medical Images from Slices Automatically Landmarked with Growing Neural Models

In this study, we utilise a novel approach to segment out the ventricular system in a series of high resolution T1-weighted MR images. We present a brain ventricles fast reconstruction method. The method is based on the processing of brain sections and establishing a fixed number of landmarks onto those sections to reconstruct the ventricles 3D surface. Automated landmark extraction is accomplished through the use of the self-organising network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates the classical surface reconstruction and filtering processes. The proposed method offers higher accuracy compared to methods with similar efficiency as Voxel Grid.

Business Models for Cloud Computing: Experiences from Developing Modeling & Simulation as a Service Applications in Industry

The potential of cloud computing is gaining significant interest in Modeling & Simulation (M&S). The underlying concept of using computing power as a utility is very attractive to users that can access state-of-the-art hardware and software without capital investment. Moreover, the cloud computing characteristics of rapid elasticity and the ability to scale up or down according to workload make it very attractive to numerous applications including M&S. Research and development work typically focuses on the implementation of cloud-based systems supporting M&S as a Service (MSaaS). Such systems are typically composed of a supply chain of technology services. How is the payment collected from the end-user and distributed to the stakeholders in the supply chain? We discuss the business aspects of developing a cloud platform for various M&S applications. Business models from the perspectives of the stakeholders involved in providing and using MSaaS and cloud computing are investigated and presented.

Teacher educators: proposing new professional development models within an English further education context

At a time of increasing public and government focus on the quality of teacher education, little is known about the professional development needs of those who teach teachers in further education (FE). Yet they are crucial players. Efforts are intensifying across a significant number of countries to promote the professional development of teacher educators, but there is little support for new or experienced practitioners and no substantive professional standards regarding this role in English FE. This has an impact on the professional practice and career trajectories of teacher educators themselves. Based on a series of semi-structured interviews, an online survey and focus groups, this mixed-methods study uses a sequential exploratory design. The study captures the voices of English FE teacher educators who identified mentoring, induction and a choice of continuous professional development sessions as important strategies to improve the effectiveness of their role over time. This article will propose flexible models of professional development, following an analysis of new and experienced teacher educators’ needs in FE in England. The article recommends that new professional standards for teacher educators could be written collaboratively by practitioners, within a policy and institutional framework which supports the scholarship and research requirements of teacher educators.