Abstract
It is quite important and difficult for doctors to detect pathologic regions of prostate ultrasonic images. An automated region detection algorithm is proposed to solve this problem, especially for ultrasonic images containing all kinds of noise and speckle. First, all the pixels of an ultrasonic image are fired by Pulse Coupled Neural Network (PCNN). Then after being processed by morphological closing, binary reversing and region labeling, the seeds are detected automatically using PCNN, by which the region of interest (ROI) of the ultrasonic image is detected by Region Growing. In the end, we code the ROI by pseudo-color. Detected pathologic regions can be used for further clinical inspection and quantitative analysis of ultrasonic images.
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Zhang, B., Ma, Y., Lin, D., Zhang, L. (2007). Pathologic Region Detection Algorithm for Prostate Ultrasonic Image Based on PCNN. In: Preparata, F.P., Fang, Q. (eds) Frontiers in Algorithmics. FAW 2007. Lecture Notes in Computer Science, vol 4613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73814-5_23
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DOI: https://doi.org/10.1007/978-3-540-73814-5_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73813-8
Online ISBN: 978-3-540-73814-5
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