Profiling the features of pre-segmented healthy liver CT scans: towards fast detection of liver lesions in emergency scenario

Muhammad Fermi Pasha, Kee Siew Hong, Mandava Rajeswari

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

Abstract

Automating the detection of lesions in liver CT scans requires a high performance and robust solution. With CT-scan start to become the norm in emergency department, the need for a fast and efficient liver lesions detection method is arising. In this paper, we propose a fast and evolvable method to profile the features of pre-segmented healthy liver and use it to detect the presence of liver lesions in emergency scenario. Our preliminary experiment with the MICCAI 2007 grand challenge datasets shows promising results of a fast training time, ability to evolve the produced healthy liver profiles, and accurate detection of the liver lesions. Lastly, the future work directions are also presented.

Original languageEnglish
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages5169-5173
Number of pages5
DOIs
Publication statusPublished - 2011
Externally publishedYes
EventInternational Conference of the IEEE Engineering in Medicine and Biology Society 2011 - Boston, United States of America
Duration: 30 Aug 20113 Sep 2011
Conference number: 33rd
https://ieeexplore.ieee.org/xpl/conhome/6067544/proceeding (Proceedings)

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

ConferenceInternational Conference of the IEEE Engineering in Medicine and Biology Society 2011
Abbreviated titleEMBC 2011
CountryUnited States of America
CityBoston
Period30/08/113/09/11
Internet address

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