Overview of Positron Emission Tomography (PET) for Brain Functions Degeneration Classification

摘要

Positron Emission Tomography scans show metabolic changes that occur in an organ or tissue at the cellular level. This is important because at the cellular level the disease always starts. Computed Tomography scans and Magnetic Resonance Images are not able to reveal cell-level problems. So, Positron Emission Tomography scans can detect changes in the cells very early, but the others detect changes as a disease affects the organs or tissue structure. Since it rises, Positron Emission Tomography gained a serious role in the diagnosis and treatment of brain disorders such as Alzheimer’s disease, Parkinson’s and Dementia, in addition to tumors. Because of the high level of chemical activity that exists in abnormal tissues such as cancer cells, these cells will show up as bright spots on these scans. This can play a major role in the diagnostic process if modern image processing methods are used to identify bright areas, as it will assist specialists in the diagnostic process and monitor the pathological condition during the treatment period. In this paper we summarize the most prominent methods used in processing positron images, starting from the traditional stages through to machine learning techniques and then to deep learning that occupies a large area in recent days.