TY - JOUR
T1 - Computer aided diagnosis (CAD) for thorax radiography children patient with segmentation deformable models method
AU - Seftina, R.
AU - Prawito, P.
AU - Soejoko, D. S.
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2018/11/19
Y1 - 2018/11/19
N2 - This study developed a correlation test Computer Aided Diagnosis (CAD) radiographic of children pulmonary using segmentation Deformable Models method to detect abnormalities. Deformable Models method searched abnormalities by value of the image pixel. Deformable models method used two variations, namely deformable models with median filter and deformable models with wiener filter. Abnormal result lung pixel values of segmentation wiener deformable models with wiener filter is 186-255 and deformable models with median filter is 190-255. Deformable Models used wiener filter have ROC result relatively higher than Deformable models used median filter with value of accuracy 78.5%, sensitivity 74.5%, specificity 80.0%, precision 90.0% and overall error of 21.0%. ROC result of segmentation using Deformable models method evince that Deformable models method can separated normal and abnormal tissue from radiographic of children pulmonary. However, Deformable models method can not definitively determine lung infection from radiographic of children pulmonary but this method can help radiologist to separated normal and abnormal tissue automatically with computer.
AB - This study developed a correlation test Computer Aided Diagnosis (CAD) radiographic of children pulmonary using segmentation Deformable Models method to detect abnormalities. Deformable Models method searched abnormalities by value of the image pixel. Deformable models method used two variations, namely deformable models with median filter and deformable models with wiener filter. Abnormal result lung pixel values of segmentation wiener deformable models with wiener filter is 186-255 and deformable models with median filter is 190-255. Deformable Models used wiener filter have ROC result relatively higher than Deformable models used median filter with value of accuracy 78.5%, sensitivity 74.5%, specificity 80.0%, precision 90.0% and overall error of 21.0%. ROC result of segmentation using Deformable models method evince that Deformable models method can separated normal and abnormal tissue from radiographic of children pulmonary. However, Deformable models method can not definitively determine lung infection from radiographic of children pulmonary but this method can help radiologist to separated normal and abnormal tissue automatically with computer.
UR - http://www.scopus.com/inward/record.url?scp=85057896971&partnerID=8YFLogxK
U2 - 10.1088/1757-899X/432/1/012054
DO - 10.1088/1757-899X/432/1/012054
M3 - Conference article
AN - SCOPUS:85057896971
SN - 1757-8981
VL - 432
JO - IOP Conference Series: Materials Science and Engineering
JF - IOP Conference Series: Materials Science and Engineering
IS - 1
M1 - 012054
T2 - 1st Materials Research Society-Indonesia Conference and Congress 2017, MRS-INA C and C 2017
Y2 - 8 October 2017 through 12 October 2017
ER -