TY  - CONF
A1  - Al-Absi, H.R.H.
A1  - Samir, B.B.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84887531406&doi=10.1063%2f1.4826054&partnerID=40&md5=0f0e94a55d195dafc7df3a26c20d0154
EP  - 2527
VL  - 1558
Y1  - 2013///
SN  - 0094243X
N1  - cited By 0; Conference of 11th International Conference of Numerical Analysis and Applied Mathematics 2013, ICNAAM 2013 ; Conference Date: 21 September 2013 Through 27 September 2013
N2  - This paper presents a computer aided diagnosis for lung nodules in CT images. The system consists of feature extraction, feature selection and classification. A two-step feature selection process is introduced to reduce the number of coefficients produced in the feature extraction step. This helps in enhancing the classification performance as it removes unneeded and redundant information. The classification rate of the system reached 98.10  with minimum false negatives and zero false positives. © 2013 AIP Publishing LLC.
SP  - 2524
ID  - scholars3344
TI  - A statistical feature selection method for lung cancer classification in CT scans
CY  - Rhodes
AV  - none
ER  -