Tony Sahama

Effects of CT image segmentation methods on the accuracy of long bone 3D reconstructions

An accurate and accessible image segmentation method is in high demand for generating 3D bone models from CT scan data, as such models are required in many areas of medical research. Even though numerous sophisticated segmentation methods have been published over the years, most of them are not readily available to the general research community. Therefore, this study aimed to quantify the accuracy of three popular image segmentation methods, two implementations of intensity thresholding and Canny edge detection, for generating 3D models of long bones. In order to reduce user dependent errors associated with visually selecting a threshold value, we present a new approach of selecting an appropriate threshold value based on the Canny filter. A mechanical contact scanner in conjunction with a microCT scanner was utilised to generate the reference models for validating the 3D bone models generated from CT data of five intact ovine hind limbs. When the overall accuracy of the bone model is considered, the three investigated segmentation methods generated comparable results with mean errors in the range of 0.18-0.24 mm. However, for the bone diaphysis, Canny edge detection and Canny filter based thresholding generated 3D models with a significantly higher accuracy compared to those generated through visually selected thresholds. This study demonstrates that 3D models with sub-voxel accuracy can be generated utilising relatively simple segmentation methods that are available to the general research community.

Sharing with Care: An Information Accountability Perspective

Health information sharing has become a vital part of modern healthcare delivery. E-health technologies provide efficient and effective ways to share medical information, but they also raise issues over which medical professionals and consumers have no control. Information security and patient privacy are key impediments that hinder sharing data as sensitive as health information. Additionally, health information interoperability hinders the adoption of available e-health technologies. Here, the authors propose an information accountability solution combining the HL7 interoperability standard and social networks for manipulating personal health records.

Cloud computing for healthcare research information sharing

With the widespread application of healthcare Information and Communication Technology (ICT), constructing a stable and sustainable data sharing circumstance has attracted rapidly growing attention in both academic research area and healthcare industry. Cloud computing is one of long dreamed visions of Healthcare Cloud (HC), which matches the need of healthcare information sharing directly to various health providers over the Internet, regardless of their location and the amount of data. In this paper, we discuss important research tool related to health information sharing and integration in HC and investigate the arising challenges and issues. We describe many potential solutions to provide more opportunities to implement EHR cloud. As well, we introduce the development of a HC related collaborative healthcare research example, thus illustrating the prospective of applying Cloud Computing in the health information science research.

Sample size considerations and augmentation of computer experiments

Computer Experiments, consisting of a number of runs of a computer model with different inputs, are now common-place in scientific research. Using a simple fire model for illustration some guidelines are given for the size of a computer experiment. A graph is provided relating the error of prediction to the sample size which should be of use when designing computer experiments. Methods for augmenting computer experiments with extra runs are also described and illustrated. The simplest method involves adding one point at a time choosing that point with the maximum prediction variance. Another method that appears to work well is to choose points from a candidate set with maximum determinant of the variance covariance matrix of predictions.

Computer Experiment: A Case Study for Modelling and Simulation of Manufacturing Systems

Abstract Deterministic computer simulation of physical experiments is now a common technique in science and engineering. Often, physical experiments are too time consuming, expensive or impossible to conduct. Complex computer models or codes, rather than physical experiments, lead to the study of computer experiments, which are used to investigate many scientific phenomena. A computer experiment consists of a number of runs of the computer code with different input choices. Design and Analysis of Computer Experiments is a rapidly growing technique in statistical experimental design. This paper aims to discuss some practical issues when designing a computer simulation and/or experiments for manufacturing systems. A case study approach is reviewed and presented.

Motivations, expectations and experiences of Australian rural and regional planners

Despite playing an extremely important role in shaping communities, the role and contribution of planners is not widely understood or acknowledged. At the same time, there is a shortage of planners in Australia, especially in non-urban areas. Thus, through an online survey of 185 rural and regional planners, this research explores the motivations, expectations and experiences of these planners. Most enjoyed and felt confident in their role, explaining that they valued the relaxed family orientated rural lifestyle and the varied nature of the planning work. Although they sometimes felt isolated, the non-urban location provided quicker progression to senior roles, the ability to engage directly with the community and to see the consequences of their decisions. Only half felt their education had prepared them well for their role, citing gaps in terms of computerised modelling, team leadership and conflict resolution skills. Their feedback centred on providing a more practical course, focusing more on regional planning, and encouraging urban and rural experience placements. As the first study to quantifiably explore rural and regional Australian planners’ perceptions of their role and challenges, the findings illustrate current experiences, key planning challenges, perceived educational gaps and future priorities.

An Architecture for Trustworthy Open Data Services

This paper addresses the development of trust in the use of Open Data through incorporation of appropriate authentication and integrity parameters for use by end user Open Data application developers in an architecture for trustworthy Open Data Services. The advantages of this architecture scheme is that it is far more scalable, not another certificate-based hierarchy that has problems with certificate revocation management. With the use of a Public File, if the key is compromised; it is a simple matter of the single responsible entity replacing the key pair with a new one and re-performing the data file signing process. Under this proposed architecture, the Open Data environment does not interfere with the internal security schemes that might be employed by the entity. However, this architecture incorporates, when needed, parameters from the entity, e.g. person who authorized publishing as Open Data, at the time that datasets are created/added.

Principles of Information Accountability: An eHealth Perspective

Information accountability is seen as a mode of usage control on the Web. Due to its many dimensions, information accountability has been expressed in various ways by computer scientists to address security and privacy in recent times. Information accountability is focused on how users participate in a system and the underlying policies that govern the participation. Healthcare is a domain in which the principles of information accountability can be utilised well. Modern health information systems are Internet based and the discipline is called eHealth. In this paper, the authors identify and discuss the goals of accountability systems and present the principles of information accountability. They characterise those principles in eHealth and discuss them contextually. They identify the current impediments to eHealth in terms of information privacy issues of eHealth consumers together with information usage requirements of healthcare providers and show how information accountability can be used in a healthcare context to address these needs. The challenges of implementing information accountability in eHealth are also discussed in terms of our efforts thus far.

Information accountability and Health Big Data Analytics: A consent-based model

With the ever increasing amount of eHealth data available from various eHealth systems and sources, Health Big Data Analytics promises enticing benefits such as enabling the discovery of new treatment options and improved decision making. However, concerns over the privacy of information have hindered the aggregation of this information. To address these concerns, we propose the use of Information Accountability protocols to provide patients with the ability to decide how and when their data can be shared and aggregated for use in big data research. In this paper, we discuss the issues surrounding Health Big Data Analytics and propose a consent-based model to address privacy concerns to aid in achieving the promised benefits of Big Data in eHealth.

Delegation of access in an information accountability framework for eHealth

Shared eHealth records systems offer promising benefits for improving healthcare through high availability of information and improved decision making; however, their uptake has been hindered by concerns over the privacy of patient information. To address these privacy concerns while balancing the requirements of healthcare professionals to have access to the information they need to provide appropriate care, the use of an Information Accountability Framework (IAF) has been proposed. For the IAF and so called Accountable-eHealth systems to become a reality, the framework must provide for a diverse range of users and use cases. The initial IAF model did not provide for more diverse use cases including the need for certain users to delegate access to another user in the system to act on their behalf while maintaining accountability. In this paper, we define the requirements for delegation of access in the IAF, how such access policies would be represented in the Framework, and implement and validate an expanded IAF model.