Vexcel Corporation proposes to design and develop a cross-platform software solution for interactive visualization and analysis of multidimensional biomedical data. There are many products for data visualization and analysis on the market today, but none that truly achieve cross-platform ubiquity. Vexcel proposes a solution that will preclude the need for users to learn a propriety fourth generation programming language. We will employ a visual programming paradigm instead, allowing users to intuitively learn the product. By defining a simplistic Application Programming Interface, Vexcel will enable incorporation of custom algorithms written in virtually any popular programming language. Where computational speed is important, Vexcel will implement algorithms optimized to the native computing environment. Vexcel's software product will encompass an innovative wavelet-based algorithm for automated co-registration of 3-D biomedical imagery. We have developed software for extracting the multi-scale edges of 2-D images and have proposed the application of this technique to automated registration of stereo images. By extrapolating our algorithm to the 3-D domain, we propose a solution to the problem of automated 3-D co- registration of MRI and CT. Cases will focus on 3-D registration for brain tumor radiation therapy planning, time-study of Multiple Sclerosis plaques and brain aneurism visualization.
The software we propose to design and develop has numerous applications in both research and commercial data analysis problems. The foundation level mathematical and visualization components will be simple to employ for many general multidimensional data analysis problems such as signal and image processing, case study data visualization and statistical analysis. In a Phase II opportunity, diverse custom vertical products could be developed for applications such as biomedical signal analysis, signal and image feature extraction and remote sensing image processing. Future applications of Vexcel's automated 3-D registration algorithm could focus on the automated integration of PET information with CT and/or MRI for brain function and development research, with applications in many mental health study areas including Alzheimer's disease, schizophrenia and attention deficit hyperactivity disorder.
