Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/27671
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dc.contributor.authorChakroun, Imen-
dc.contributor.authorMICHIELS, Nick-
dc.contributor.authorWuyts, Roel-
dc.date.accessioned2019-01-31T08:05:25Z-
dc.date.available2019-01-31T08:05:25Z-
dc.date.issued2018-
dc.identifier.citation2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE,-
dc.identifier.isbn9781538654880-
dc.identifier.urihttp://hdl.handle.net/1942/27671-
dc.description.abstractCellProfiler excels at bridging the gap between advanced image analysis algorithms and scientists who lack computational expertise. It lacks however high performance capabilities needed for High Throughput Imaging experiments where workloads reach hundreds of TB of data and are computationally very demanding. In this work, we introduce a GPU-accelerated CellProfiler where the most time-consuming algorithmic steps are executed on Graphics Processing Units. Experiments on a benchmark dataset showed significant speedup over both single and multi-core CPU versions. The overall execution time was reduced from 9.83 Days to 31.64 Hours.-
dc.description.sponsorshipThis work was supported by the VLAIO industrial R&D project ImmCyte. The NVIDIA Corporation generously, donated a GPU.-
dc.language.isoen-
dc.publisherIEEE-
dc.subject.otherCellProfiler; High Throughput Imaging; Graphics Processing Units; High Performance Computing-
dc.titleGPU-accelerated CellProfiler-
dc.typeProceedings Paper-
local.bibliographicCitation.conferencedate3-6 December 2018-
local.bibliographicCitation.conferencenameIEEE International Conference on Bioinformatics and Biomedicine (BIBM)-
local.bibliographicCitation.conferenceplaceMadrid, Spain-
local.format.pages6-
local.bibliographicCitation.jcatC1-
dc.description.notesChakroun, I (reprint author), IMEC, Exasci Life Lab, 75 Kapeldreef, B-3001 Leuven, Belgium. imen.chakroun@imec.be; nick.michiels@uhasselt.be; roel.wuyts@imec.be-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
dc.identifier.doi10.1109/BIBM.2018.8621271-
dc.identifier.isi000458654000057-
local.bibliographicCitation.btitle2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)-
item.contributorChakroun, Imen-
item.contributorMICHIELS, Nick-
item.contributorWuyts, Roel-
item.accessRightsRestricted Access-
item.fullcitationChakroun, Imen; MICHIELS, Nick & Wuyts, Roel (2018) GPU-accelerated CellProfiler. In: 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE,.-
item.fulltextWith Fulltext-
item.validationecoom 2020-
item.validationvabb 2021-
Appears in Collections:Research publications
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