Non-invasive neuroimaging techniques enable extraordinarily sensitive and specific in vivo study of the structure, functional response and connectivity of biological mechanisms. With these advanced methods comes a heavy reliance on computer-based processing, analysis and interpretation. While the neuroimaging community has produced many excellent academic and commercial tool packages, new tools are often required to interpret new modalities and paradigms. Developing custom tools and ensuring interoperability with existing tools is a significant hurdle. To address these limitations, we present a new framework for algorithm development that implicitly ensures tool interoperability, generates graphical user interfaces, provides advanced batch processing tools, and, most importantly, requires minimal additional programming or computational overhead. Java-based rapid prototyping with this system is an efficient and practical approach to evaluate new algorithms since the proposed system ensures that rapidly constructed prototypes are actually fully-functional processing modules with support for multiple GUI's, a broad range of file formats, and distributed computation. Herein, we demonstrate MRI image processing with the proposed system for cortical surface extraction in large cross-sectional cohorts, provide a system for fully automated diffusion tensor image analysis, and illustrate how the system can be used as a simulation framework for the development of a new image analysis method. The system is released as open source under the Lesser GNU Public License (LGPL) through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC).

SUMMARYThis paper presents a cable-driven dexterous manipulator with a large, open lumen. One specific application for the manipulator is the treatment of the degeneration of bone tissue (osteolysis) during a less-invasive hip revision surgery. Rigid tools used in traditional approaches limit the surgeons' ability to comprehensively treat the osteolysis due to the complex geometries of the lesion. The surgical scenario, testing, kinematic modeling, and image-based inverse kinematics are described. Testing shows 94% coverage of a lesion wall; the kinematic model describes manipulator notch positions within 0.15 mm, while the image-based inverse kinematics has 0.36 mm error. This manipulator is potentially useful in treating osteolytic lesions through (1) effective lesion exploration compared to conventional techniques, and (2) rapidly performing inverse kinematics from visual feedback.

The recent developments in depth-imaging and 3D computer vision techniques allow efficient and real-time acquisition, reconstruction, and understanding of the 3D environment, which enable an array of life-like and immersive applications. We show here an excerpt of some of the key technologies spanning sensors, algorithms, and system integration based on depth imaging and 3D sensing technology. The small form factor, the low power and the real-time depth image capture are the key enablers. We talk here about emerging trends in this burgeoning field and new enabled applications that include immersive and interactive gaming, virtual home and office decoration, virtual cloth fitting, video conferencing with custom background and synthetic environment, education and training, and numerous other new entertainment and productivity usages with natural and intuitive interactions.

A novel algorithm is presented to segment and reconstruct injected bone cement from a sparse set of X-ray images acquired at arbitrary poses. The sparse X-ray multi-view active contour (SxMAC—pronounced “smack”) can 1) reconstruct objects for which the background partially occludes the object in X-ray images, 2) use X-ray images acquired on a noncircular trajectory, and 3) incorporate prior computed tomography (CT) information. The algorithm’s inputs are preprocessed X-ray images, their associated pose information, and prior CT, if available. The algorithm initiates automated reconstruction using visual hull computation from a sparse number of X-ray images. It then improves the accuracy of the reconstruction by optimizing a geodesic active contour. Experiments with mathematical phantoms demonstrate improvements over a conventional silhouette based approach, and a cadaver experiment demonstrates SxMAC’s ability to reconstruct high contrast bone cement that has been injected into a femur and achieve sub-millimeter accuracy with four images.