Interactive processing and visualization of image data for biomedical and life science applications

Oliver G Staadt,Gunther H Weber,Vijay Natarajan,David F Wiley,Bernd Hamann

doi:10.1186/1471-2121-8-s1-s10

Abstract

BackgroundApplications in biomedical science and life science produce large data sets using increasingly powerful imaging devices and computer simulations. It is becoming increasingly difficult for scientists to explore and analyze these data using traditional tools. Interactive data processing and visualization tools can support scientists to overcome these limitations.ResultsWe show that new data processing tools and visualization systems can be used successfully in biomedical and life science applications. We present an adaptive high-resolution display system suitable for biomedical image data, algorithms for analyzing and visualization protein surfaces and retinal optical coherence tomography data, and visualization tools for 3D gene expression data.ConclusionWe demonstrated that interactive processing and visualization methods and systems can support scientists in a variety of biomedical and life science application areas concerned with massive data analysis.

Highlights

Applications in biomedical science and life science produce large data sets using increasingly powerful imaging devices and computer simulations
We have developed an imaging system based on capturing image volumes using optical coherence tomography (OCT) imaging technology
For the foveal inset image to appear aligned with the rest of the display, a homography matrix must be computed to map the foveal inset image plane to the display image plane

Summary

Introduction

Applications in biomedical science and life science produce large data sets using increasingly powerful imaging devices and computer simulations. It is becoming increasingly difficult for scientists to explore and analyze these data using traditional tools. Interactive data processing and visualization tools can support scientists to overcome these limitations. Interactive visualization techniques can support life scientists in the exploration and analysis of biological image data. Interactive visualization systems maintain a closed loop between the user and the system and, need to be very fast Building such a system requires the development of new visualization methods, and there exists need to design new and effective interaction techniques

Methods

Results

Conclusion