Pattern Recognition Letters
IEEE Transactions on Information Technology in Biomedicine
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
Simultaneous lesion segmentation and bias correction in breast ultrasound images
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Fully automated computer-aided volume estimation system for thyroid planar scintigraphy
Computers in Biology and Medicine
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Automatically extracting lesion boundaries in ultrasound images is difficult due to the variance in shape and interference from speckle noise. An effective scheme of removing speckle noise can facilitate the segmentation of ultrasonic breast lesions, which can be performed with an iterative disk expansion method. In this study, a disk expansion segmentation method is proposed to semi-automatically find lesion contours in ultrasonic breast image. To evaluate the performance of the proposed method, the simulations with seven types of cysts, three in vitro phantom images and 10 clinical breast images are introduced. The mean normalized true positive area overlap between simulated contours and contours obtained by the proposed method is over 85% in simulation results. A strong correlation exists between physicians' manual delineations and detected contours in clinical breast images. In addition, the method is also verified to be able to simultaneously contour multiple lesions in a single image. In comparison with the conventional active contour model, our proposed method does not require any initial seed within a lesion and thus, it is more convenient and applicable.