[Objective] The slope deformation is common in the mountainous areas, which significantly promotes landslide development and increases landslide risk. So, it is the important factor for the regional landslide assessment. [Methods] By reviewing literatures, the research status of regional landslide assessment integrating slope deformation characteristics were summarized. [Results] The relevant theoretical models and technical methods are not mature and are still in the stage of preliminary research. The temporal resolution of regional slope deformation should be further improved, and key characteristics of the long time series slope deformation should be captured, and the spatio-temporal distribution of regional slope deformation should be deeply analyzed. A preliminary regional landslide assessment system integrating slope deformation was constructed, including process steps, technical methods and factor indicators. The main technical methods include the qualitative judgment based on expert experience, weighted layer overlay based on expert experience and correction matrix, slope deformation as a factor index of regional landslide assessment, slope deformation as a landslide sample of regional landslide assessment. The slope deformation factor can be further divided into slope deformation type, intensity, distribution position and time change. [Conclusions] It is necessary to combine new technologies such as machine learning and artificial intelligence to propose or optimize the new quantitative regional landslide assessment models that integrate the slope deformation characteristics to improve regional landslide assessment accuracy. It is expected to promote the study on regional landslide assessment integrating slope deformation, and support the early landslide prevention in the complex mountainous areas.