Cascaded window memoization for medical imaging

Farzad Khalvati, Mehdi Kianpour, Hamid R. Tizhoosh

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Window Memoization is a performance improvement technique for image processing algorithms. It is based on removing computational redundancy in an algorithm applied to a single image, which is inherited from data redundancy in the image. The technique employs a fuzzy reuse mechanism to eliminate unnecessary computations. This paper extends the window memoization technique such that in addition to exploiting the data redundancy in a single image, the data redundancy in a sequence of images of a volume data is also exploited. The detection of the additional data redundancy leads to higher speedups. The cascaded window memoization technique was applied to Canny edge detection algorithm where the volume data of prostate MR images were used. The typical speedup factor achieved by cascaded window memoization is 4.35x which is 0.93x higher than that of window memoization.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence Applications and Innovations - 12th INNS EANN-SIG International Conference, EANN 2011 and 7th IFIP WG 12.5 International Conference, AIAI 2011, Proceedings
PublisherSpringer New York LLC
Number of pages10
EditionPART 2
ISBN (Print)9783642239595
StatePublished - 2011
Event7th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2011 - Corfu, Greece
Duration: Sep 15 2011Sep 18 2011

Publication series

NameIFIP Advances in Information and Communication Technology
NumberPART 2
Volume364 AICT
ISSN (Print)1868-4238


Conference7th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2011


  • Fuzzy memoization
  • Inter-frame redundancy
  • Performance optimization

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management


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