期刊
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
卷 89, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compmedimag.2021.101899
关键词
Computed tomography (CT); Lung nodule detection; Lung nodule segmentation; Lung nodule atlas; Statistical analysis
资金
- National Key Research and Development Program of China [2018YFC0116400]
- Science and Technology Commission of Shanghai Municipality [19QC1400600]
- National Natural Science Foundation of China [62071176]
This study presents an artificial intelligence lung image analysis system (ALIAS) for nodule detection and segmentation, analyzing differences between benign and malignant lung nodules to enhance understanding of early lung cancer diagnosis.
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 artificialintelligence 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.
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