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Resource-Centered Distributed Processing of Large Histopathology Images

Abstract : Automatic cell nuclei detection is a real challenge in medical imagery. The Marked Point Process (MPP) is one of the most promising methods. To handle large histopathology images, the algorithm has to be distributed. A new parallelization paradigm called Ordered Read-Write Locks (ORWL) is presented as a possible solution for solving some of the unwanted side effects of the distribution, namely an imprecision of the results on the internal boundaries of partitioned images. This solution extends a parallel version of MPP that has reached good speedups on GPU cards, but was not scaling to complete images as they appear in practical data.
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Submitted on : Thursday, June 2, 2016 - 2:36:23 PM
Last modification on : Tuesday, October 25, 2022 - 4:17:40 PM
Long-term archiving on: : Saturday, September 3, 2016 - 11:00:51 AM


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  • HAL Id : hal-01325648, version 1


Daniel Salas, Jens Gustedt, Daniel Racoceanu, Isabelle Perseil. Resource-Centered Distributed Processing of Large Histopathology Images. 19th IEEE International Conference on Computational Science and Engineering, Aug 2016, Paris, France. ⟨hal-01325648⟩



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