3-D Selection of Neural Pathway Estimates Using Simple Mouse Gestures

A ~100-150 word summary of the interface you plan to prototype, the hypothesis of the value that it provides the user, and how you plan to evaluate if your hypothesis is true or false. I am planning to develop a new gestural interface for 3-D selection of neural pathways estimated from MRI imaging of human brains. Selection of pathways is important to neuroscientists because it is a precursor to many forms of scientific hypothesis-generation and analysis. Existing interfaces are frustratingly inefficient, since they require the three-dimensional placement of regions-of-interest (ROIs) within the volumetric data space, using only a mouse and keyboard. The proposed system should address this inefficiency by providing an image space solution: converting simple, natural, 2-D mouse gestures into three-dimensional path selections. First, I plan to build a prototype version of the system, and use a heuristic evaluation to understand the design space. Having learned lessons from this heuristic evaluation, I hope to design and conduct a formal user study, comparing the new system to existing systems in current use. The details of this formal user study are not yet decided. TASK ANALYSIS - Who are the users? What tasks will the users need to perform? What new tasks do they desire to perform? Where are the tasks performed? How are the tasks learned? What set of tools does the user have now? How often do your users perform the tasks? What happens when things go wrong? What's the relationship between the user and his or her data? How do your users communicate with each other? With whom do they communicate? My tool is intended for neuroscientists studying the structure of the brain's white matter using Diffusion Tensor Imaging (DTI), a form of magnetic resonance imaging. Scientists are able to use DTI images to extract neural pathway estimates in individual subjects, using a set of techniques known as "white matter tractography". As part of their daily routine, scientists use computer software to analyze these pathway estimates and compare them between different subjects. I will focus on improving the critical subtask of pathway selection: identifying sets of pathways for further analysis. Tractography may produce some pathways of no interest to the neuroscientist (and that may obscure the desired pathways!) Moreover, tractography produces many false positive connection results, and the neuroscientist must use domain-specific knowledge to remove these false