TY - JOUR
T1 - Secondary Pulmonary Tuberculosis Identification Via pseudo-Zernike Moment and Deep Stacked Sparse Autoencoder
AU - Wang, Shui Hua
AU - Satapathy, Suresh Chandra
AU - Zhou, Qinghua
AU - Zhang, Xin
AU - Zhang, Yu Dong
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature B.V.
PY - 2022/3
Y1 - 2022/3
N2 - Secondary pulmonary tuberculosis (SPT) is one of the top ten causes of death from a single infectious agent. To recognize SPT more accurately, this paper proposes a novel artificial intelligence model, which uses Pseudo Zernike moment (PZM) as the feature extractor and deep stacked sparse autoencoder (DSSAE) as the classifier. In addition, 18-way data augmentation is employed to avoid overfitting. This model is abbreviated as PZM-DSSAE. The ten runs of 10-fold cross-validation show this model achieves a sensitivity of 93.33% ± 1.47%, a specificity of 93.13% ± 0.95%, a precision of 93.15% ± 0.89%, an accuracy of 93.23% ± 0.81%, and an F1 score of 93.23% ± 0.83%. The area-under-curve reaches 0.9739. This PZM-DSSAE is superior to 5 state-of-the-art approaches.
AB - Secondary pulmonary tuberculosis (SPT) is one of the top ten causes of death from a single infectious agent. To recognize SPT more accurately, this paper proposes a novel artificial intelligence model, which uses Pseudo Zernike moment (PZM) as the feature extractor and deep stacked sparse autoencoder (DSSAE) as the classifier. In addition, 18-way data augmentation is employed to avoid overfitting. This model is abbreviated as PZM-DSSAE. The ten runs of 10-fold cross-validation show this model achieves a sensitivity of 93.33% ± 1.47%, a specificity of 93.13% ± 0.95%, a precision of 93.15% ± 0.89%, an accuracy of 93.23% ± 0.81%, and an F1 score of 93.23% ± 0.83%. The area-under-curve reaches 0.9739. This PZM-DSSAE is superior to 5 state-of-the-art approaches.
KW - Deep learning
KW - Machine learning
KW - Secondary pulmonary tuberculosis
KW - Sparse autoencoder
KW - pseudo-Zernike moment
UR - http://www.scopus.com/inward/record.url?scp=85121457745&partnerID=8YFLogxK
U2 - 10.1007/s10723-021-09596-6
DO - 10.1007/s10723-021-09596-6
M3 - Article
AN - SCOPUS:85121457745
SN - 1570-7873
VL - 20
JO - Journal of Grid Computing
JF - Journal of Grid Computing
IS - 1
M1 - 1
ER -