We present a method for detecting circumscribed masses in digital mammograms. Morphological hierarchical watersheds are used in the segmentation process. Oversegmentation is prevented by employing a reconstructive open/close alternating sequential filter to simplify the image. The advantage of this method of simplification is that the object shapes and edges are preserved. The regional maxima of the simplified input image are then extracted and used as internal markers for the hierarchical watershed transform, which is applied to the gradient image of the simplified input image. An image-based classification technique is applied to reduce the number of false positives. The method is applied to 18 mammograms from the MIAS database, containing 20 circumscribed masses in background tissue of varying density. We obtain a high true detection rate using combined with a low number of false positives per image.
The aim of this study is to provide feature images of digital mammograms in which regions corresponding to masses are enhanced. Subsequently, the feature images can be segmented and classified
into two classes; masses and normal tissue. Our proposed feature extraction method is based on a local energy measure as texture feature. The local energy measure is extracted using a filter optimized with respect to the relative distance between the average feature values. In order to increase the sensitivity of the texture feature extraction scheme each mammogram is preprocessed using wavelet transformation, adaptive histogram equalization, and a morphology based enhancement technique. Initial experiments indicate that our scheme is able to provide useful feature images of digital mammograms. In order to quantify the system performance the feature images of 38 mammograms from the MIAS database -- 19 containing circumscribed masses, and 19 containing spiculated masses -- were segmented using simple gray level thresholding. For the circumscribed masses a true positive (TP) rate of 89% with a corresponding 2.3 false detections (false positives, FPs) per image was achieved. For the spiculated masses the performance was somewhat lower, yielding an overall TP rate of 84% with a corresponding 2.6 FPs per image.
By using a new method of solving the radiative transfer equation, we calculate the diffuse (i.e. scattered) radiance due to a Gaussian beam incident on a slab of finite thickness filled with scattering particles. The radiance is calculated for several observation angles and at any point inside or at the boundaries of the slab, both for isotropically and weakly anisotropically scattering media.