AUTOMATED DETECTION SYSTEM FOR LUNG MASSES AS A STAGE OF ARTIFICIAL INTELLIGENCE DEVELOPMENT IN THE DIAGNOSTICS OF LUNG CANCER
https://doi.org/10.22328/2079-5343-2018-9-3-62-68
Abstract
In the century of the fourth industrial revolution, there is a rapid progress of technological developments in medicine. Possibilities of collecting large amounts of digital information and the modern computer capacity growth are reasons for the increased attention to artificial intelligence (AI) and its role in the diagnostics and the prediction of diseases. In the diagnostics, AI aims to model the human intellectual activity, providing assistance to a practicing doctor in the processing of big data. Development of AI can be considered as a way for implementation and ensuring of national political and economic interests in the health care improvement. Lung cancer is on the first position of cancer incidences. This implies that the development and implementation of computed-aided systems for lung cancer diagnostic is very urgent and important. The article presents the results concerning the development of a computed-aided system for the lung nodule detection, which is based on the processing of computed tomography data. Perspectives of the AI application to the lung cancer diagnostics are discussed. There is a few information about a role of Russian developments in this area in foreign and domestic literature.
About the Authors
B. M. MoiseenkoRussian Federation
St. Petersburg
A. A. Meldo
Russian Federation
St. Petersburg
L. V. Utkin
Russian Federation
St. Petersburg
I. Yu. Prokhorov
Russian Federation
St. Petersburg
M. A. Ryabinin
Russian Federation
St. Petersburg
A. A. Bogdanov
Russian Federation
St. Petersburg
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Review
For citations:
Moiseenko B.M., Meldo A.A., Utkin L.V., Prokhorov I.Yu., Ryabinin M.A., Bogdanov A.A. AUTOMATED DETECTION SYSTEM FOR LUNG MASSES AS A STAGE OF ARTIFICIAL INTELLIGENCE DEVELOPMENT IN THE DIAGNOSTICS OF LUNG CANCER. Diagnostic radiology and radiotherapy. 2018;(3):62-68. (In Russ.) https://doi.org/10.22328/2079-5343-2018-9-3-62-68