A Hybrid Approach to Detection of Brain Hemorrhage Candidates from Clinical Head CT Scans
Yonghong Li, Qingmao Hu, Jianhuang Wu, Zhijun Chen · 2009
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.