NDLI: Feature extraction and classification for ultrasound images of lumbar spine with support vector machine

Content Provider	IEEE Xplore Digital Library
Author	Shuang Yu Kok Kiong Tan Ban Leong Sng Shengjin Li Sia, A.T.H.
Copyright Year	2014
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore (Shuang Yu; Kok Kiong Tan)
Abstract	In this paper, we proposed a feature extraction and machine learning method for the classification of ultrasound images obtained from lumbar spine of pregnant patients in the transverse plane. A group of features, including matching values and positions, appearance of black pixels within predefined windows along the midline, are extracted from the ultrasound images using template matching and midline detection. Support vector machine (SVM) with Gaussian kernel is utilized to classify the bone images and interspinous images with optimal separation hyperplane. The SVM is trained with 800 images from 20 pregnant subjects and tested with 640 images from a separate set of 16 pregnant patients. A high success rate (97.25% on training set and 95.00% on test set) is achieved with the proposed method. The trained SVM model is further tested on 36 videos collected from 36 pregnant subjects and successfully identified the proper needle insertion site (interspinous region) on all of the cases. Therefore, the proposed method is able to identify the ultrasound images of lumbar spine in an automatic manner, so as to facilitate the anesthetists' work to identify the needle insertion point precisely and effectively.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	4659
Ending Page	4662
File Size	3285898
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6944663
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	Ultrasonic imaging Feature extraction Support vector machines Bones Videos Training Needles
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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