A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.
|Autori:||Gori I; Bagagli F; Fantacci M; Martinez AP; Retico A; De Mitri I; Donadio S; Fulcheri C; Gargano G; Magro R; Santoro M; Stumbo S|
|Titolo:||Multi-scale analysis of lung computed tomography images|
|Anno del prodotto:||2007|
|Digital Object Identifier (DOI):||10.1088/1748-0221/2/09/P09007|
|Appare nelle tipologie:||1.1 Articolo in rivista|