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This paper develops a methodology for finding which features in a noisy image are strong enough to be distinguished from background noise. It is based on scale space, i.e. a family of smooths of the image. Pixel locations having statistically significant gradient and/or curvature are highlighted by colored symbols. The gradient version is enhanced by(More)
Accurate detection of the borders of skin lesions is a vital first step for computer aided diagnostic systems. This paper presents a novel automatic approach to segmentation of skin lesions that is particularly suitable for analysis of dermoscopic images. Assumptions about the image acquisition, in particular, the approximate location and color, are used to(More)
BACKGROUND AND PURPOSE Diffusion-weighted imaging and dynamic first-pass bolus tracking of susceptibility contrast agents (perfusion imaging) are two new magnetic resonance imaging techniques that offer the possibility of early diagnosis of stroke. The present study was performed to evaluate the diagnostic information derived from these two methods in a rat(More)
UNLABELLED The relatively low specificity of dynamic contrast-enhanced T1-weighted magnetic resonance imaging (MR) imaging of breast cancer has lead several groups to investigate different approaches to data acquisition, one of them being the use of rapid T2*-weighted imaging. Analyses of such data are difficult due to susceptibility artifacts and breathing(More)
BACKGROUND It is often difficult to differentiate early melanomas from benign melanocytic nevi even by expert dermatologists, and the task is even more challenging for primary care physicians untrained in dermatology and dermoscopy. A computer system can provide an objective and quantitative evaluation of skin lesions, reducing subjectivity in the(More)
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Summary SiZer (SIgnificant ZERo crossing of the derivatives) and SiNos (SIgnificant NOnSta-tionarities) are scale-space based visualization tools for statistical(More)