Lung nodule detection in low-dose and thin-slice computed tomography |
| |
Authors: | Retico A Delogu P Fantacci M E Gori I Preite Martinez A |
| |
Institution: | Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, Largo Pontecorvo 3, 56127 Pisa, Italy. retico@df.unipi.it |
| |
Abstract: | A computer-aided detection (CAD) system for the identification of small pulmonary nodules in low-dose and thin-slice CT scans has been developed. The automated procedure for selecting the nodule candidates is mainly based on a filter enhancing spherical-shaped objects. A neural approach based on the classification of each single voxel of a nodule candidate has been purposely developed and implemented to reduce the amount of false-positive findings per scan. The CAD system has been trained to be sensitive to small internal and sub-pleural pulmonary nodules collected in a database of low-dose and thin-slice CT scans. The system performance has been evaluated on a data set of 39 CT containing 75 internal and 27 sub-pleural nodules. The FROC curve obtained on this data set shows high values of sensitivity to lung nodules (80-85% range) at an acceptable level of false positive findings per patient (10-13 FP/scan). |
| |
Keywords: | Computer-aided detection (CAD) Low-dose computed tomography (LDCT) Thin-slice CT Image processing |
本文献已被 ScienceDirect PubMed 等数据库收录! |