NDLI: Filament tracking and encoding for complex biological networks

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Filament tracking and encoding for complex biological networks

Content Provider	ACM Digital Library
Author	Mayerich, David M. Keyser, John
Abstract	We present a framework for segmenting and storing filament networks from scalar volume data. Filament structures are commonly found in data generated using high-throughput microscopy. These data sets can be several gigabytes in size because they are either spatially large or have a high number of scalar channels. Filaments in microscopy data sets are difficult to segment because their diameter is often near the sampling resolution of the microscope, yet single filaments can span large data sets. We describe a novel method to trace filaments through scalar volume data sets that is robust to both noisy and under-sampled data. We use a GPU-based scheme to accelerate the tracing algorithm, making it more useful for large data sets. After the initial structure is traced, we can use this information to create a bounding volume around the network and encode the volumetric data associated with it. Taken together, this framework provides a convenient method for accessing network structure and connectivity while providing compressed access to the original volumetric data associated with the network.
Starting Page	353
Ending Page	358
Page Count	6
File Format	PDF
ISBN	9781605581064
DOI	10.1145/1364901.1364952
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2008-06-02
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Microscopy Segmentation Volumetric Fiber
Content Type	Text
Resource Type	Article

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