MRI Image Processing Based on Fractal Analysis.

Background: Cancer is one of the most common causes of human mortality, with about 14 million new cases and 8.2 million deaths reported in in 2012. Early diagnosis of cancer through screening allows interventions to reduce mortality.

Evaluation of Machine Learning Algorithm Utilization for Lung Cancer Classification Based on Gene Expression Levels.

Background: Lung cancer remains one of the most common cancers in the world, both in terms of new cases (about 13% of total per year) and deaths (nearly one cancer death in five), because of the high case fatality. Errors in lung cancer type or malignant growth determination lead to degraded treatment efficacy, because anticancer strategy depends on tumor morphology.

Materials And Methods: We have made an attempt to evaluate effectiveness of machine learning algorithms in the task of lung cancer classification based on gene expression levels.

[Intelligent distributed system of population cancer screening].

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.

[Automated identification, interpretation and classification of focal changes in the lungs on the images obtained at computed tomography for lung cancer screening].

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.