Digital image processing
An Introduction to Digital Image Processing
An Introduction to Digital Image Processing
Self-Organizing Maps
Texture guided active appearance model propagation for prostate segmentation
MICCAI'10 Proceedings of the 2010 international conference on Prostate cancer imaging: computer-aided diagnosis, prognosis, and intervention
Computer Methods and Programs in Biomedicine
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Traditional segmentation methods cannot provide satisfying results for extraction of prostate gland from Transrectal Ultrasound (TRUS) images because of the presence of strong speckle noise and shadow artifacts. Most ultrasound image segmentation techniques that adopt model-based approach such as active contour are considered semi-automatic because they require initial seeds or contours to be manually identified. In this paper, we propose a method for automatic segmentation of prostate using feature-based self organizing map (SOM). Median filtering and top hat transform are first applied to remove speckle noise. A technique is developed to remove ultrasound-specific speckles using texture-based thresholding. An SOM algorithm is employed to identify prostate pixels taking spatial information, gray-level as well as texture information to form its input vector. The clustered image is then processed to produce a fully connected prostate contour. A number of experiments comparing extracted contours with manually-delineated contours validated the performance of our method.