Title :
A Hybrid Approach to Detection of Brain Hemorrhage Candidates from Clinical Head CT Scans
Author :
Li, Yonghong ; Hu, Qingmao ; Wu, Jianhuang ; Chen, Zhijun
Author_Institution :
Shenzhen Inst. of Adv. Integration Technol., Chinese Acad. of Sci., Hong Kong, China
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.
Keywords :
biological tissues; brain; computerised tomography; diseases; image classification; medical image processing; Otsu thresholding; candidate brain hemorrhage region detection; clinical head CT scan; computed tomography; fuzzy C-means clustering; hierarchical FCM thresholding; knowledge-based classification system; maximum entropy; nonbrain tissues; Blood; Cardiac disease; Computational modeling; Computed tomography; Entropy; Head; Hemorrhaging; Hopfield neural networks; Simulated annealing; Spatial resolution; CT scans; hemorrhage detection; maximum entropy;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
DOI :
10.1109/FSKD.2009.717
