Bringing the algorithms to the data: Cloud-based benchmarking for medical image analysis

Allan Hanbury, Henning Müller, Georg Langs, Marc André Weber, Bjoern H. Menze, Tomas Salas Fernandez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

23 Scopus citations


Benchmarks have shown to be an important tool to advance science in the fields of information analysis and retrieval. Problems of running benchmarks include obtaining large amounts of data, annotating it and then distributing it to the participants of a benchmark. Distribution of the data to participants is currently mostly done via data download that can take hours for large data sets and in countries with slow Internet connections even days. Sending physical hard disks was also used for distributing very large scale data sets (for example by TRECvid) but also this becomes infeasible if the data sets reach sizes of 5-10 TB. With cloud computing it is possible to make very large data sets available in a central place with limited costs. Instead of distributing the data to the participants, the participants can compute their algorithms on virtual machines of the cloud providers. This text presents reflections and ideas of a concrete project on using cloud-based benchmarking paradigms for medical image analysis and retrieval. It is planned to run two evaluation campaigns in 2013 and 2014 using the proposed technology.

Original languageEnglish
Title of host publicationInformation Access Evaluation
Subtitle of host publicationMultilinguality, Multimodality, and Visual Analytics - Third International Conference of the CLEF Initiative, CLEF 2012, Proceedings
Number of pages6
StatePublished - 2012
Externally publishedYes
Event3rd International Conference of the CLEF Initiative, CLEF 2012 - Rome, Italy
Duration: 17 Sep 201220 Sep 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7488 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference3rd International Conference of the CLEF Initiative, CLEF 2012


  • anatomy detection
  • benchmark
  • case-based medical information retrieval
  • cloud computing
  • medical image analysis


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