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Two finalists were selected from the top 10th percentile of over 500 abstracts submitted to the annual meeting of the Society’s annual meeting, who then made competitive podium presentations judged by the ASB Awards Committee. The award consists of an engraved plaque and a check for $1,000.
The ASB was founded in October 1977 by a group of 53 scientists and clinicians, and its first annual meeting was held that year in Iowa City. The ASB mission is to encourage and foster the exchange of information and ideas among biomechanists working in different disciplines and fields of application and to facilitate the development of biomechanics as a basic and applied science.
Thomas is a graduate research assistant in the Department of Orthopaedics and Rehabilitation, as well as a PhD candidate in the Department of Biomedical Engineering at The University of Iowa. His presentation was entitled “Virtual pre-operative reconstruction planning for comminuted articular fractures,” co-authored by Donald D. Anderson, J. Lawrence Marsh, and Thomas D. Brown (University of Iowa), and by Andrew R. Willis (University of North Carolina at Charlotte).
Also at the annual meeting, Donald Anderson, research associate professor of orthopaedics and rehabilitation, and biomedical engineering, was elected president of the ASB.
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Student Yunfeng Sui traveled to the IEEE International Workshop on 3-D Digital Imaging and Modeling held on October 3-4, 2009 in Kyoto, Japan. Here he presented a paper entitled Virtual 3D Bone Fracture Reconstruction via Inter-Fragmentary Surface Alignment which details how this task is accomplished. The system takes as input a collection of bone fragment models represented as surface meshes, typically segmented from CT data. Users interact with fragment models in a virtual environment to reconstruct the fracture. In contrast to other approaches that are either completely automatic or completely interactive, the system attempts to strike a balance between interaction and automation. There are two key fracture reconstruction interactions: (1) specifying matching surface regions between fragment pairs and (2) initiating pairwise and global fragment alignment optimizations. Each match includes two fragment surface patches hypothesized to correspond in the reconstruction. Each alignment optimization initialized by the user triggers a 3D surface registration which takes as input: (1) the specified matches and (2) the current position of the fragments. The proposed system leverages domain knowledge via user interaction, and incorporates recent advancements in surface registration, to generate fragment reconstructions that are more accurate than manual methods and more reliable than completely automatic methods.
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Experimental Low-Cost LIDAR Scanner Implementation Complete
The UNCC Machine Vision lab has acquired an AR4000 range sensor from Acuity Laser Measurement the system is capable of capturing 3D surface range data up to 40 feet from the sensor.
We have recently develop a linux driver for this sensor. The source for this driver is available through subversion at the subversion repository here under the link "laser-driver." The linux driver is currently compatible with linux kernel versions 2.6.16-2.8.18.
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Small Code Footprint DICOM Image Loader Completed
Recent work involving medical images have motivated the implementation of a robust DICOM image reader. This work has now been completed resulting in one of the most complete open-source Java implementations of the DICOM specification. The implementation is capable of loading 8-bit grayscale, 8-bit color, 16-bit grayscale, and 24-bit color DICOM images where the image data may be uncompressed, run-length encoded, jpeg-lossless compressed, or jpeg-lossy compressed. Also of interest is the implementation of the spatial (sequential) lossless encoding mode (SOF3) of the ISO/IEC also known as JPEGL. Note that this IS NOT an implementation of JPEG-LS. It is an implementation of the original lossless JPEG coding scheme as specified in the ORIGINAL JPEG Internal Standards Organization (ISO) spec :
- ISO/IS-10918-1 (JPEG Part 1)
- ISO/IS-10918-2 (JPEG Part 2)
Whereas JPEG-LS is ISO spec ISO/IS-14495-1 (JPEG-LS Part 1).
I can find no easy-to-use, small-footprint, open-source Java implementation capable of decoding these streams at full resolution. Some nice things about the implementation is that it requires just a few new classes to run (approximately 6).
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