Elena V. Zudilova-Seinstra

Trends in interactive visualization: State-of-the-art survey

The purpose of Interactive Visualization is to develop new scientific methods to increase scientists abilities to explore data and to understand better the results of experiments based on extensive calculations. These techniques not only provide users with a possibility to view the data but also permit them to use interaction capabilities to interrogate and navigate through datasets and communicate these insights. This book is a unique multi-disciplinary collection of scientific articles, which provides readers with insight in Interactive Visualization from various perspectives, representing the state-of-the-art with the special emphasis on: Advanced visualization algorithms and methods, Interactive data exploration, Display systems and interaction techniques, Multi-modal and collaborative visualization, Design and evaluation of interactive visualization tools and systems, Various application topics.

The effect of stereoscopy and motion cues on 3D interpretation task performance

We study the effectiveness of stereoscopy and smooth motion as 3D cues for medical interpretation of vascular structures as obtained by 3D medical imaging techniques. We designed a user study where the user has to follow a path in a mazelike solid shaded 3D structure. The user controls rotation of the model. We measure user performance in terms of time taken and error rate. The experiment was executed with 32 (medical and non-medical) users. The results show that motion cue is more important than stereoscopy, and that stereoscopy has no added value when motion is already present, which is not consistent with previous experiments.

On the role of individual human abilities in the design of adaptive user interfaces for scientific problem solving environments

A scientific problem solving environment should be built in such a way that users (scientists) might exploit underlying technologies without a specialised knowledge about available tools and resources. An adaptive user interface can be considered as an opportunity in addressing this challenge. This paper explores the importance of individual human abilities in the design of adaptive user interfaces for scientific problem solving environments. In total, seven human factors (gender, learning abilities, locus of control, attention focus, cognitive strategy and verbal and nonverbal IQs) have been evaluated regarding their impact on interface adjustments done manually by users. People’s preferences for different interface configurations have been investigated. The experimental study suggests criteria for the inclusion of human factors into the user model guiding and controlling the adaptation process. To provide automatic means of adaptation, the Intelligent System for User Modelling has been developed.

Evaluation of 2D and 3D glove input applied to medical image analysis

We describe a series of experiments that compared 2D/3D input methods for selection and positioning tasks related to medical image analysis. For our study, we chose a switchable P5 Glove Controller, which can be used to provide both 2DOF and 6DOF input control. Our results suggest that for both tasks the overall performance and accuracy can be improved when the input device with more degrees of freedom (DOF) is used for manipulation of the visualized medical data. 3D input turned out to be more beneficial for the positioning task than for the selection task. In order to determine a potential source of the difference in the task completion time between 2D and 3D input, we also investigated whether there was a significant difference between 2DOF and 6DOF input methods with regard to the time spent on task-specific basic manipulations.

Overview of Interactive Visualisation

The book starts with the chapter presenting a comprehensive overview of Interactive Visualization. The chapter introduces fundamentals of Interactive Visualization, surveys research in the field, examines existing challenges and provides information about popular frameworks that can be used for the development of interactive data visualizations.

Exploring individual user differences in the 2D/3D interaction with medical image data

User-centered design is often performed without regard to individual user differences. In this paper, we report results of an empirical study aimed to evaluate whether computer experience and demographic user characteristics would have an effect on the way people interact with the visualized medical data in a 3D virtual environment using 2D and 3D input devices. We analyzed the interaction through performance data, questionnaires and observations. The results suggest that differences in gender, age and game experience have an effect on people’s behavior and task performance, as well as on subjective user preferences.

Service-oriented visualization applied to medical data analysis

With the era of Grid computing, data driven experiments and simulations have become very advanced and complicated. To allow specialists from various domains to deal with large datasets, aside from developing efficient extraction techniques, it is necessary to have available computational facilities to visualize and interact with the results of an extraction process. Having this in mind, we developed an Interactive Visualization Framework, which supports a service-oriented architecture. This framework allows, on one hand visualization experts to construct visualizations to view and interact with large datasets, and on the other hand end-users (e.g., medical specialists) to explore these visualizations irrespective of their geographical location and available computing resources. The image-based analysis of vascular disorders served as a case study for this project. The paper presents main research findings and reports on the current implementation status.

Visualisation and interaction for scientific exploration and knowledge discovery

With the rapid development of information technology, the amount and complexity of scientific data increase exponentially every day. The data explosion has led to very large detailed datasets and the amount of detail in these datasets continues to grow. Nowadays, the challenge is to harness the power of knowledge hidden in the collage of scientific data. Visualisation technologies empower users to perceive important patterns in the data, identify areas that need further scrutiny and make sophisticated decisions. However, looking at information is only the first step in understanding. For some domains, it is unclear what the features of interest are and how to define them in such a way that they can be detected. Many scientific discovery tasks can only be solved in interactive ways: by combining information analysis tools, advanced visualisation techniques and intuitive user interfaces. The importance of human interaction and perception cannot be ignored in the field of scientific computing and data analysis. Interactive exploration systems allow people to examine scientific data and share obtained knowledge with, and through, information technology. These systems should be easy to use and not require sophisticated computer skills, as most of users are rather domain-specific experts than computer scientists. To increase users’ abilities to explore the data and better understand the results of experiments based on extensive calculations, new scientific methods need to be developed and applied. This special issue combines papers that discuss how modern visualisation and interaction techniques can augment the information analysis cycle from the user’s perspective. The collected manuscripts are updated and expanded versions of papers presented at a series of

Exploring 2D/3D Input Techniques for Medical Image Analysis

We describe a series of experiments that compared the 2D and 3D input methods for selection and positioning tasks related to medical image analysis. For this study, we chose a switchable P5 Glove Controller, which can be used to provide both 2DOF and 6DOF input control. Our results suggest that for both tasks the overall completion time and accuracy can be improved when the input device with more degrees of freedom is used for manipulation of the visualized medical data. However, 3D input appeared to be more beneficial for the positioning task than for the selection task.

Automated quantification of arterial stenosis on CE-MRA by using a deformable vascular tubular model

Accurate arterial stenosis quantification is important for the decision of a proper treatment in patients suffering atherosclerotic disease. We have developed an automated arterial stenosis quantification method by using a deformable tubular 3D model that fits into luminal vasculature particularly in severe stenoses.