Radiation-induced microstructural defects cause degradation of mechanical properties and a life time reduction of reactor structural components during nuclear power plant operation. The effect of neutron irradiation fluence and flux, neutron spectrum, corrosion environment, etc. on mechanical properties is investigated under the NPP's surveillance programs and additional nuclear material research. The material strength typically increases while ductility and fracture toughness decrease after neutron irradiation. Transmission Electron Microscopy is one of the methods for Post Irradiation Examination (PIE) which helps to understand the material behaviour exposed to different reactor operating conditions. Therefore, such PIE methods are important to develope and optimize. In this study, we introduce the specimen preparation methodology and radiation-induced damage (RID) evaluation of stainless steel SSRT test specimens by the means of Scanning and Transmission Electron Microscopy (SEM, TEM). In austenitic microstructure, Frank interstitial dislocation loops, cavities or voids and radiation-induced precipitates are the dominant RID evolved under neutron irradiation. Futhermore, the material susceptibility to segregation related to the IASCC mechanism is widely studied within 300-series stainless steels. The proper determination of RID size distribution refers to degradation mechanisms in reactor materials. In our research, the RID characterization is demonstrated on the specimens irradiated to ~ 15 dpa in PWR conditions. Distribution of cavities, Frank loops and radiation-induced precipitates were evaluated in bright/dark field kinematical conditions and through-focal series. The nature of cavities, i. e. voids/He or H stabilized bubbles with the size less than 3 nm, was not recognized in the specimens prepared by standard electrolytic polishing method. Radiation-induced segregation in a narrow area up to 10 nm was detected by point STEM-EDS analysis. To evaluate RID size distribution, the automatic image-processing program was developed and compared to the visual analysis. So far, the results were optimized on Frank loops and precipitates and are in a good agreement with the manual processing.