Herwig Rehatschek

Wikipedia – challenges and new horizons in enhancing medical education

BackgroundWikipedia gains growing attention as a provider of health information. This study aimed to investigate the use, relevance and challenges of Wikipedia among medical students.MethodsAn online questionnaire was made accessible to students at five medical universities in Germany, Austria, and Norway. Besides demographical data, the questions covered the role of Wikipedia in the academic life of medical students. The questionnaire investigated if the students had ever found erroneous medical entries and whether they corrected these.ResultsA frequent use of Wikipedia in general is statistically significant correlated with a frequent use in medical studies (p < 0.001). Information retrieved from Wikipedia is predominantly critically appraised either by comparing it to profound knowledge (79%) and/or to specific literature (75%). Despite most (97%) respondents disclosed that they already had found false information in Wikipedia, recognized errors were seldomly corrected (~20%).ConclusionsThe information retrieved from Wikipedia is critically appraised. However, we found shortcomings in handling erroneous entries. We argue for professional responsibility among medical students in dealing with this dynamic resource. Moreover, we encourage medical schools to supplement information to Wikipedia to further benefit from the vast possibilities of this platform.

Optimized mean shift algorithm for color segmentation in image sequences

The application of the mean shift algorithm to color image segmentation has been proposed in 1997 by Comaniciu and Meer. We apply the mean shift color segmentation to image sequences, as the first step of a moving object segmentation algorithm. Previous work has shown that it is well suited for this task, because it provides better temporal stability of the segmentation result than other approaches. The drawback is higher computational cost. For speed up of processing on image sequences we exploit the fact that subsequent frames are similar and use the cluster centers of previous frames as initial estimates, which also enhances spatial segmentation continuity. In contrast to other implementations we use the originally proposed CIE LUV color space to ensure high quality segmentation results. We show that moderate quantization of the input data before conversion to CIE LUV has little influence on the segmentation quality but results in significant speed up. We also propose changes in the post-processing step to increase the temporal stability of border pixels. We perform objective evaluation of the segmentation results to compare the original algorithm with our modified version. We show that our optimized algorithm reduces processing time and increases the temporal stability of the segmentation.

Virtual European School-VES

The Virtual European School (VES) is an ongoing European project-funded by the Educational Multimedia Task Force initiative of the European Union-with the aim to develop a comprehensive online resource of teaching material for secondary school education. The system will be fed by a group of smaller publishing houses from different European countries (Austria, Italy, Greece, Great Britain) specialising in educational material. The offer will contain multimedia material, CBT products, and also additional background materials, such as passages from schoolbooks, or Internet resources. The technical structure of the VES system will be based on Internet technologies, with interconnected VES servers in each participating region. The multimedia material will be stored in a database, with multilingual annotations for each project. There exist three user groups within the VES: publishers, teachers and pupils.

Rushes video summarization using a collaborative approach

This paper describes the video summarization system developed by the partners of the K-Space European Network of Excellence for the TRECVID 2008 BBC rushes summarization evaluation. We propose an original method based on individual content segmentation and selection tools in a collaborative system. Our system is organized in several steps. First, we segment the video, secondly we identify relevant and redundant segments, and finally, we select a subset of segments to concatenate and build the final summary with video acceleration incorporated. We analyze the performance of our system through the TRECVID evaluation.

Identifying Different Settings in a Visual Diary

We describe an approach to identifying specific settings in large collections of photographs corresponding to a visual diary. An algorithm developed for setting detection should be capable of clustering images captured at the same real world locations (e.g. in the dining room at home, in front of the computer in the office, in the park, etc.). This requires the selection and implementation of suitable methods to identify visually similar backgrounds in images using their visual features. The goal of the work reported here is to automatically detect settings in images taken over a single week. We achieve this using scale invariant feature transform (SIFT) features and X-means clustering. In addition, we also explore how the use of location based metadata can aid this process.

The introduction of a new virtual microscope into the eLearning platform of the Medical University of Graz

In 2002 the Medical University of Graz (MUG) introduced its first Learning Management System (LMS). One of the first applications developed was a virtual microscope 1.0 (VM 1.0) to be used by students via a standard web browser. The basic idea was to offer the functionality of a microscope via an interactive application which is integrated within the LMS. The main advantages of that concept were saving costs, enhancing the flexibility for students and utilizing additional features and possibilities offered by new media. Cost saving was achieved by replacing hundreds of expensive physical microscopes by the virtual microscope, which can be used on any PC with a standard web browser. After more than 8 years the technology as well as the functionality of the VM 1.0 was now out-dated. We describe the stages to introduce a VM 2.0 within VMC/Moodle in order to help other universities who want to introduce a VM for their students to speed up the decision process and to avoid possible traps.

A Generic Annotation Model for Video Databases

The change from analogue broadcasting to digital MPEG-2 channels among the satellite programs resulted in new demands on video databases and archives. Digital archives offer on the one hand a reduction of storage costs, and enable on the other hand easy reuse of already existing material. However, searching for appropriate film material in large archives is still a tedious problem. This paper describes a generic annotation model for MPEG movies which enables the user to structure the film in as many hierarchical levels as needed and to annotate any physical or logical part of the film with generic definable attributes. The model was implemented in prototype system which additionally offers a query and ordering facility per web browser and Internet.

Comparing fact finding tasks and user survey for evaluating a video browsing tool

There are still no established methods for the evaluation of browsing and exploratory search tools. In the (multimedia) information retrieval community evaluations following the Cranfield paradigm (as e.g. used in TRECVID) have been widely adopted. We have applied two TRECVID style fact finding approaches (retrieval and question answering tasks) and a user survey to the evaluation of a video browsing tool. We analyze the correlation between the results of the different methods, whether different aspects can be evaluated independently with the survey, and if a learning effect can be measured with the different methods. The results show that the retrieval task correlates better with the user experience according to the survey than the question answering tasks. It turns out that the survey rather measures the general user experience while different aspects of the usability cannot be analyzed independently.

An innovative system for formulating complex, combined content-based and keyword-based queries

We propose a search & retrieval (S&R) tool, which supports the combination of a text search with content-based search for video and image content. This S&R system allows the formulation of complex queries allowing the arbitrary combination of content-based and text-based query elements with logical operators. The system will be implemented as a client/server system. The entire S&R system is designed in such a way that the client system can be either a web application accessing the server over the Internet or a native client with local access to the server. The S&R tool is embedded into a system called MECiTV - Media Collaboration for iTV. Within MECiTV a complete authoring environment for iTV content will be developed. The proposed S&R tool will enable iTV authors and content producers to efficiently search for already existing material in order to reduce costs for iTV productions.

Introduction of OER at the Medical University of Graz: Practical tips to introduce OER with a minimum of additional budget and efforts

The two buzzwords Open Educational Resources (OER) and Massive Open Online Courses (MOOC) are in the scientific community now common terms which are very well known. This implies for universities that these two trends have become a part of their reputation. However, usually no additional budget is given to universities for the proper implementation of OERs. In our paper we outline a cost and resource efficient way to introduce OER and give some practical tips what has to be considered.