Paper Info
Title
A Hybrid Approach to Detection of Brain Hemorrhage Candidates from Clinical Head CT Scans
Abstract
In this paper we present an approach for detecting brain hemorrhage regions from clinical head computed tomography (CT) scans. Firstly, non-brain tissues are removed by thresholding based on Fuzzy C-means (FCM) clustering. Then, thresholding based on maximum entropy is employed for the candidate hemorrhage region detection. Finally, non-hemorrhage regions and other normal artifacts are differentiated from hemorrhage regions by a knowledge-based classification system. The approach has been validated against 30 clinical brain CT images and compared with Otsu thresholding as well as hierarchical FCM thresholding.
Year
DOI
Venue
2009
10.1109/FSKD.2009.717
FSKD (1)
Keywords
Field
DocType
brain hemorrhage candidates,brain hemorrhage region,clinical head ct scan,candidate hemorrhage region detection,computerised tomography,clinical brain ct image,diseases,candidate brain hemorrhage region detection,hybrid approach,fuzzy c-means,hemorrhage region,computed tomography,ct scans,nonbrain tissues,hemorrhage detection,otsu thresholding,knowledge-based classification system,hierarchical fcm thresholding,image classification,clinical head,brain,clinical head ct scans,brain hemorrhage candidate,biological tissues,maximum entropy,medical image processing,fuzzy c-means clustering,head,biomedical imaging,histograms,knowledge base,entropy,ct scan,knowledge based systems,classification system
Histogram,Computer vision,Pattern recognition,Medical imaging,Computer science,Fuzzy logic,Knowledge-based systems,Artificial intelligence,Principle of maximum entropy,Thresholding,Contextual image classification,Cluster analysis
Conference
Volume
ISBN
Citations 
1
978-0-7695-3735-1
2
PageRank 
References 
Authors
0.40
6
4
Name
Order
Citations
PageRank
Yong-Hong Li171.21
Qingmao Hu216019.73
Jianhuang Wu36011.75
Zhijun Chen4131.62