NDLI: Application of Inductive Learning in Human Brain CT Image Recognition

Content Provider	IEEE Xplore Digital Library
Author	Xi-Zhao Wang Wei-Xi Lin
Copyright Year	2007
Description	Author affiliation: Hebei Univ., Baoding (Xi-Zhao Wang)
Abstract	This paper presented three ways utilized to do head CT (Computed Tomography) image Computer Aided Diagnosis and their performance comparison, and analysis of the performance comparison. In this present work, we collected 116 normal pieces of head CT image and 96 abnormal ones, and utilized two ways to do feature extraction, and applied the ways of decision tree, RBFNN and outlier detection in classification. At the same time, it was implied in this paper that one question formulation could lead to different question solutions by utilizing different methods. The question formulation is the base of measure which we make use of. For this point of view, the question formulation is more important than question solution. Meanwhile, as future work, we will try to find different formulations of this question by making different question solutions as guidance. So we can achieve more conclusions of the question, and can select optimal solution in greater scope.
Starting Page	1667
Ending Page	1671
File Size	1284304
Page Count	5
File Format	PDF
ISBN	9781424409723
DOI	10.1109/ICMLC.2007.4370415
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Humans Computed tomography Image recognition Head Application software Image analysis Performance analysis Feature extraction Decision trees Classification tree analysis Outlier detection CT image Texture Symmetry Decision tree RBFNN
Content Type	Text
Resource Type	Article

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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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