RESUMO
This review summarizes data dedicated to improving the efficiency of screening of malignant tumors through the use of modern information and telecommunication technologies. It is showed that currently available software solutions in the field of medical imaging is not enough adapted for population screening. So far there is no single standard that defines checking algorithms of data processing at certain controlled conditions. The most expected result will be the organization of information centralized storage, sharing diagnostic data, providing broad access to them, automated analysis and selection of diagnostically significant results through the software. The basic requirements for the development of self-learning systems for intelligent processing array of heterogeneous data through the use of technologies of semantic networks are provided.
Assuntos
Inteligência Artificial/tendências , Redes de Comunicação de Computadores , Diagnóstico por Imagem/tendências , Detecção Precoce de Câncer , Programas de Rastreamento , Software , Algoritmos , Redes de Comunicação de Computadores/estatística & dados numéricos , Detecção Precoce de Câncer/métodos , Detecção Precoce de Câncer/tendências , Humanos , Programas de Rastreamento/métodos , Programas de Rastreamento/tendênciasRESUMO
This review article analyzes data of literature devoted to the description, interpretation and classification of focal (nodal) changes in the lungs detected by computed tomography of the chest cavity. There are discussed possible criteria for determining the most likely of their character--primary and metastatic tumor processes, inflammation, scarring, and autoimmune changes, tuberculosis and others. Identification of the most characteristic, reliable and statistically significant evidences of a variety of pathological processes in the lungs including the use of modern computer-aided detection and diagnosis of sites will optimize the diagnostic measures and ensure processing of a large volume of medical data in a short time.