NDLI: Fully automated localization of multiple pelvic bone structures on MRI

Content Provider	IEEE Xplore Digital Library
Author	Onal, S. Lai-Yuen, S. Bao, P. Weitzenfeld, A. Hart, S.
Copyright Year	2014
Description	Author affiliation: Dept. of Ind. & Manuf. Eng., Southern Illinois Univ. - Edwardsville, Edwardsville, IL, USA (Onal, S.) \|\| Coll. of Med. Obstetrics & Gynecology, Univ. of South Florida, Tampa, FL, USA (Hart, S.) \|\| Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA (Bao, P.; Weitzenfeld, A.) \|\| Dept. of Ind. & Manage. Syst. Eng., Univ. of South Florida, Tampa, FL, USA (Lai-Yuen, S.)
Abstract	In this paper, we present a fully automated localization method for multiple pelvic bone structures on magnetic resonance images (MRI). Pelvic bone structures are currently identified manually on MRI to identify reference points for measurement and evaluation of pelvic organ prolapse (POP). Given that this is a time-consuming and subjective procedure, there is a need to localize pelvic bone structures without any user interaction. However, bone structures are not easily differentiable from soft tissue on MRI as their pixel intensities tend to be very similar. In this research, we present a model that automatically identifies the bounding boxes of the bone structures on MRI using support vector machines (SVM) based classification and non-linear regression model that captures global and local information. Based on the relative locations of pelvic bones and organs, and local information such as texture features, the model identifies the location of the pelvic bone structures by establishing the association between their locations. Results show that the proposed method is able to locate the bone structures of interest accurately. The pubic bone, sacral promontory, and coccyx were correctly detected (DSI > 0.75) in 92%, 90%, and 88% of the testing images. This research aims to enable accurate, consistent and fully automated identification of pelvic bone structures on MRI to facilitate and improve the diagnosis of female pelvic organ prolapse.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	3353
Ending Page	3356
File Size	731513
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6944341
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Magnetic resonance imaging Bladder Support vector machines Pelvic bones Computed tomography Biomedical imaging
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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