Region growing method using edge sharpness for brain ventricle detection
Chulho Won, Dong Hun Kim · 2007
In this paper, an algorithm that can define the threshold value automatically in region growing is proposed in order to detect a brain ventricle using a wavelet transform in MRI brain images. After the wavelet transform, edge sharpness, which means the average magnitude of detail signals on the contour of the object, was computed by using the magnitude of horizontal and vertical detail signals. The contours of a brain ventricle were detected by increasing the threshold value repeatedly and computing edge sharpness. When the edge sharpness became maximal, the optimal threshold was determined, and the detection of a brain ventricle was accomplished finally. This paper suggests an algorithm that can detect a brain ventricle; compares that algorithm with the geodesic active contour model numerically and visually by applying real MRI brain images; and verifies the efficiency of the proposed algorithm.