0000000000963454
AUTHOR
G Forni
A completely automated CAD system for mass detection in a large mammographic database.
Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing secon…
Liver stiffness, a non-invasive marker of liver disease: a core study group report
The ability to evaluate liver stiffness non-invasively in clinical practice by measuring transient elastography using FibroScan® has resulted in considerable interest and enthusiasm. A core study group, organized by the Italian Association for the Study of the Liver, has assessed the usefulness of FibroScan® in the diagnosis and management of liver disease in clinical practice. The group concluded that FibroScan® is a valuable, non-invasive technique and have developed a consensus report form for registering transient elastography results. In this article, we report the findings of the study group.