Exploring Online Nuclear Segmentation on Large Fluorescence Brain Tumor Images using CometCloud
نویسندگان
چکیده
A bottleneck of histopathology image segmentation is its execution speed and memory capacity for large images containing hundreds and thousands of objects, such as cells. In this paper we propose an approach to perform online nuclear segmentation on large fluorescence brain tumor images using CometCloud, an autonomic Cloud Engine. Based on our previously developed cellular segmentation algorithm, the seed detection and contour generation were parallelized on CometCloud, using the HPC infrastructure available at Rutgers University. The method was tested on some fluorescence brain tumor images (4096x4096x3), containing thousands of nuclei within each image. We have achieved more than 100 times speed up compared to the original sequential implementation.
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تاریخ انتشار 2013