Augmented Reality Interactive Enhancements for Scientific Data Visualization and Manipulation

Decision making in biomedical and clinical imaging research is predominantly based on analyzing two-dimensional (2D) images, such as generated by Magnetic Resonance Imaging (MRI), Computerized Tomography (CT), or histopathological imaging. Evaluating the complexity of the entire three-dimensional (3D) structure, however, requires reconstructing a stack of 2D images into a 3D scene. Recent advances in Augmented Reality (AR) offer the potential to facilitate this challenging task interactively and flexibly, particularly for biomedical and clinical 3D data visualization applications. 

Our goal is to develop an AR system platform and methodology for 3D data recognition, visualization and manipulation using HoloLens (Microsoft, USA).  This innovative AR implementation and pipeline will be validated with NIH clinical imaging, and evaluated for clinical diagnosis applications.

The BESIP student will gain valuable hands-on experience in research areas including biomedical engineering, medical imaging, and computer vision. The student will also learn a wide-range of skills and methods associated with AR implementation, image processing, and technology development. 

Basser lab: The Section on Quantitative Imaging and Tissue Sciences (SQITS) is dedicated to inventing and developing quantitative MRI biomarkers to follow key processes in normal and abnormal development, disease, degeneration, and trauma, motivated by fundamental research into the basis of functional properties of brain and extracellular matrix (ECM). This group produces large numbers of multi-slice images using various MRI methodologies.

Pohida group: Provides electrical, electronic, electro-optical, mechanical, computer, and software engineering expertise to NIH projects that require in-house technology development. Collaborations involve advanced signal transduction and data acquisition; real-time signal and image processing; control and monitoring systems (e.g., robotics and process automation); and rapid prototype development. Collaborations result in the design of first-of-a-kind biomedical/clinical research systems, instrumentation, and methodologies.