Quick breast cancer detection via classification of evoked EEG potentials in the mammologist's brain

Electroencephalography is a method of testing the electrical activity of the brain by jointly processing electrical signals registered at several points on the surface of the skull. It was originally invented to study mechanisms by which human behavior is generated, in particular, for brain diseases diagnosis. However, in the past decades, electroencephalography has become the basis of many brain-computer interfaces, which decode neural response to different stimuli into commands that, for instance, operate external devices. Our research is concerned with another purpose of analyzing responses of a multi-channel electroencephalogram (EEG) to outward stimuli. It is assumed that the person whose EEG is processed is an experienced mammologist able to reliably distinguish between X-ray mammograms of women with breast cancer and those of healthy women. These studies pursue the aim to essentially improve productivity of rare pronounced experts by way of, first, accelerating the screening of mammographic images up to ten pictures per second, and, second, immediately detecting the eventual potentials evoked in the expert's EEG by a target (cancer) image among a crowd of nontarget ones before the expert becomes aware of this fact.