MicroCT image coding based on air filtering

Joan Bartrina-Rapesta, Marc Navarro, Juan Muñoz-Gómez, Michael W. Marcellin, Jesús Ruberte, Joan Serra-Sagristà

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


Preclinical images are a fundamental tool for many areas of medical research including cancer detection and drug development. Usually, Micro Computed Tomography (MicroCT) images are acquired to evaluate skeleton malformations after a genetic alteration of an animal. Such images have very high resolution and need to be compressed to reduce hard disk space and transmission time. However, like other CT images, the acquisition process introduces noise in the resulting image, which prevents most modern coding systems, including JPEG2000, from obtaining good coding performance. In this work, we do not address noise filtering as such, but we focus on an air filtering approach - inspired by the biological nature of the captured MicroCT images - aimed to improve the coding performance. Extensive experimental tests using different images suggest that air filtering does not penalize the diagnosis process of experts (measured in Mean Opinion Score), nor the visual quality, while allowing substantial improvements in coding performance.

Original languageEnglish (US)
Title of host publicationProceedings - DCC 2012
Subtitle of host publication2012 Data Compression Conference
Number of pages1
StatePublished - 2012
Event2012 Data Compression Conference, DCC 2012 - Snowbird, UT, United States
Duration: Apr 10 2012Apr 12 2012

Publication series

NameData Compression Conference Proceedings
ISSN (Print)1068-0314


Other2012 Data Compression Conference, DCC 2012
Country/TerritoryUnited States
CitySnowbird, UT


  • Image coding
  • MicroCT
  • air filtering

ASJC Scopus subject areas

  • Computer Networks and Communications


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