TY - JOUR
T1 - An artificial-intelligence lung imaging analysis system (ALIAS) for population-based nodule computing in CT scans
AU - Chen, Liyun
AU - Gu, Dongdong
AU - Chen, Yanbo
AU - Shao, Ying
AU - Cao, Xiaohuan
AU - Liu, Guocai
AU - Gao, Yaozong
AU - Wang, Qian
AU - Shen, Dinggang
N1 - Funding Information:
This work was partially supported by the National Key Research and Development Program of China ( 2018YFC0116400 ), the Science and Technology Commission of Shanghai Municipality ( 19QC1400600 ) and the National Natural Science Foundation of China ( 62071176 ).
Publisher Copyright:
© 2021
PY - 2021/4
Y1 - 2021/4
N2 - Computed tomography (CT) screening is essential for early lung cancer detection. With the development of artificial intelligence techniques, it is particularly desirable to explore the ability of current state-of-the-art methods and to analyze nodule features in terms of a large population. In this paper, we present an artificial-intelligence lung image analysis system (ALIAS) for nodule detection and segmentation. And after segmenting the nodules, the locations, sizes, as well as imaging features are computed at the population level for studying the differences between benign and malignant nodules. The results provide better understanding of the underlying imaging features and their ability for early lung cancer diagnosis.
AB - Computed tomography (CT) screening is essential for early lung cancer detection. With the development of artificial intelligence techniques, it is particularly desirable to explore the ability of current state-of-the-art methods and to analyze nodule features in terms of a large population. In this paper, we present an artificial-intelligence lung image analysis system (ALIAS) for nodule detection and segmentation. And after segmenting the nodules, the locations, sizes, as well as imaging features are computed at the population level for studying the differences between benign and malignant nodules. The results provide better understanding of the underlying imaging features and their ability for early lung cancer diagnosis.
KW - Computed tomography (CT)
KW - Lung nodule atlas
KW - Lung nodule detection
KW - Lung nodule segmentation
KW - Statistical analysis
UR - http://www.scopus.com/inward/record.url?scp=85102842850&partnerID=8YFLogxK
U2 - 10.1016/j.compmedimag.2021.101899
DO - 10.1016/j.compmedimag.2021.101899
M3 - Article
C2 - 33761446
AN - SCOPUS:85102842850
SN - 0895-6111
VL - 89
JO - Computerized Medical Imaging and Graphics
JF - Computerized Medical Imaging and Graphics
M1 - 101899
ER -
