Introduction and objective: Computer Aided Decision (CAD) systems based on Medical Imaging could support radiologists in grading Hepatocellular carcinoma (HCC) by means of Computed Tomography (CT) images, avoiding medical invasive procedures such as biopsies. The identification and characterization of Regions of Interest (ROIs) containing lesions is an important phase allowing an easier classification in two classes of HCCs. Two steps are needed for the detection of lesioned ROIs: a liver isolation in each CT slice and a lesion segmentation.
A novel approach for Hepatocellular Carcinoma detection and classification based on triphasic CT Protocol / Bevilacqua, Vitoantonio; Brunetti, Antonio; Trotta, Gianpaolo Francesco; Dimauro, Giovanni; Elez, Katarina; Alberotanza, Vito; Scardapane, Arnaldo. - (2017), pp. 1856-1863. (Intervento presentato al convegno IEEE Congress on Evolutionary Computation, CEC 2017 tenutosi a Donostia-San Sebastian, Spain nel June 5-8, 2017) [10.1109/CEC.2017.7969527].
A novel approach for Hepatocellular Carcinoma detection and classification based on triphasic CT Protocol
Bevilacqua, Vitoantonio;Brunetti, Antonio;Trotta, Gianpaolo Francesco;
2017-01-01
Abstract
Introduction and objective: Computer Aided Decision (CAD) systems based on Medical Imaging could support radiologists in grading Hepatocellular carcinoma (HCC) by means of Computed Tomography (CT) images, avoiding medical invasive procedures such as biopsies. The identification and characterization of Regions of Interest (ROIs) containing lesions is an important phase allowing an easier classification in two classes of HCCs. Two steps are needed for the detection of lesioned ROIs: a liver isolation in each CT slice and a lesion segmentation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
