Computer-assisted shape classification of middle cerebral artery aneurysms for surgical planning

Derek Burrows, Chad Washington, Ralph Dacey, Tao Ju

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

Abstract

We present a method for classifying the shape of middle cerebral artery (MCA) aneurysms using segmented surfaces from angiograms. The classification follows a set of visual criteria established by experienced surgeons to group aneurysms based on the clipping strategies used in surgery. Starting from a centerline representation of the input, our method automatically classifies the input into one of 4 types using a combination of graph analysis and supervised learning. When evaluated on a cohort of 84 subjects, our method achieves between 60% to 69% expected classification accuracy (p < 10-3) with zero to a moderate amount of input from novice users.

Original languageEnglish
Title of host publication2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1311-1315
Number of pages5
ISBN (Electronic)9781467319591
StatePublished - Jul 29 2014
Externally publishedYes
Event2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 - Beijing, China
Duration: Apr 29 2014May 2 2014

Publication series

Name2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

Conference

Conference2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
CountryChina
CityBeijing
Period04/29/1405/2/14

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  • Cite this

    Burrows, D., Washington, C., Dacey, R., & Ju, T. (2014). Computer-assisted shape classification of middle cerebral artery aneurysms for surgical planning. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 (pp. 1311-1315). [6868118] (2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014). Institute of Electrical and Electronics Engineers Inc..