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Comparing Vascular Visualization Techniques with Gamification

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Comparing Vascular Visualization Techniques with Gamification

Titov, Andrey (2020) Comparing Vascular Visualization Techniques with Gamification. Masters thesis, Concordia University.

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Abstract

One of the bottlenecks of visualization research is the lack of volunteers for studies that evaluate new methods and paradigms. However, with the technological advancement in mobile hardware and the availability of online marketplaces, it has become possible to perform user studies using the gamification paradigm. Furthermore, the possibility of implementing volume rendering, a computationally expensive method, on mobile devices opened the door to the use of gamification in the context of medical image visualization studies.

In this thesis, we describe a gamified study that we performed with the goal of comparing several cerebrovascular visualization techniques. The study was implemented in the form of a mobile game, "Connect Brain", that was developed and distributed on both Android and iOS platforms. Connect Brain features two mini-games, one of which asks the player to make decisions about the depth of different vessels, and the second one that has them determine if two vessels are connected. The gameplay data was sent to a server and analyzed to determine the most effective visualization techniques.

The results of our study confirmed that fog, chroma-depth and pseudo chromdepth are among the most effective depth perception cues, similar to previous studies. However, our results differed for the edge enhancement cue, which we found to be one of the worst in terms of depth perception. The gamification paradigm, which allowed us to collect more data samples from more participants than similar studies, had more similar results to the larger studies. This suggests the importance of having a large number of subjects and trials when evaluating visualization paradigms.

Although gamification presented some challenges, we believe that this technique has great potential for future studies in not only medical image visualization but for the other clinical tasks.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (Masters)
Authors:Titov, Andrey
Institution:Concordia University
Degree Name:M. Comp. Sc.
Program:Computer Science
Date:17 December 2020
Thesis Supervisor(s):Kersten-Oertel, Marta
Keywords:Medical Image Visualization, Volume Visualization, Depth Cues, Angiography, Gamification, Mobile Games
ID Code:987821
Deposited By: Andrey Titov
Deposited On:23 Jun 2021 16:39
Last Modified:23 Jun 2021 16:39
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