An eustachian valve (EV) remnant, if present, is usually noted by the presence of a thin ridge or a crescent-shaped fold of endocardium arising from the anterior rim of the inferior vena cava orifice due to the persistence of the right sinus venosus valve. Though the embryologic explanation of cor triatriatum dexter (CTD) is the same as that of the normal formation of the EV--lack of regression of the right sinus venosus valve--it is usually called CTD or divided right atrium when there are attachments on the atrial septum giving the appearance of a divided atrium. However, it's called prominent eustachian valve when the right sinus venosus valve has partly regressed, with no remaining septal attachments and without the appearance of a divided atrium. We present the case of an adult patient with an atrial septal defect with a high insertion of a giant EV, which mimics the echocardiographic appearance of divided right atrium.

Self-administration of metallic mercury through the intravenous route is rare. This event has been reported in psychiatric patients and in suicide attempts. We report a case of successive intravenous self-injections of mercury demonstrated by plain film radiographs and CT scans of the thorax and abdomen.

In this paper, we present a new approach to the segmentation and analysis of solid breast nodules in ultrasonography. We have applied computer vision techniques to segment the nodules and analyze a series of diagnostic criteria, which can help discriminate malignant and benignant tumors. The segmentation is carried out by means of a combination of a region growing algorithm and the active contour technique. On the other hand, the analysis of the diagnostic criteria involves several methods, such as the extraction of the minimum distance ellipse through gradient descent, pseudocorner location or structure tensor. The methods that we propose have provided quite satisfactory results and show the usefulness of image processing techniques in the diagnosis by means of medical imaging. The aim of this work is not the substitution of the specialist, but the generation of a series of parameters which reduce the need of carrying out the biopsy. D

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In this paper, we present a new approach to the segmentation and analysis of solid breast nodules in ultrasonography. We have applied computer vision techniques to segment the nodules and analyze a series of diagnostic criteria which can help discriminate malignant and benignant tumors. The segmentation is carried out in a semiautomatic way, whereas the analysis of the diagnostic criteria involves several computational methods. The techniques which we propose have provided quite satisfactory results and show the usefulness of image processing in the diagnosis through medical imaging.