NDLI: Localization of a linear structure object in medical images based on hidden Markov model

Content Provider	IEEE Xplore Digital Library
Author	Xu Tao Xing Hancheng
Copyright Year	2003
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Nanjing Univ. of Aeronaut. & Astronaut., China (Xu Tao)
Abstract	In this paper a novel approach to localization of a linear structure object (spine) in medical images using one-dimensional hidden markov model is proposed. Feature sequence of a linear structure object is extracted by using a horizontal-line sampling window with fixed width along the central axis of the object in training phase and the model training is performed through maximum likelihood estimation provided by the Baum-Welch algorithm. A specific localization method derived from Viterbi algorithm is presented for determining a feature sequence in a test image, from which the position of a linear structure object could be obtained The use of heuristic information improves obviously the performance of localization and the computational complexity. The experiments demonstrate the effectiveness in localization application based on the simple feature expression and the proposed localization method.
Sponsorship	IEEE Comput. Soc. Tech. Committee on Computational Med. Mount Sinai School of Med. Dept. Anesthesiology Texas Tech. Univ. College of Eng
Starting Page	317
Ending Page	322
File Size	268560
Page Count	6
File Format	PDF
ISBN	0769519016
ISSN	10637125
DOI	10.1109/CBMS.2003.1212808
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-06-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biomedical imaging Hidden Markov models Object recognition Image sampling Active appearance model Computer science Biomedical engineering Image processing Feature extraction Vectors
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Computer Science Applications

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