Histopathology is considered one of the most important tools for diagnosis in medical routine. It is characterized by the study of structural and morphological changes of the cells, caused by diseases in biological tissues. The use of computational techniques in the processing of histopathological images allows the identification of structural elements as well as the determination of inherent characteristics, supporting the study of the structural organization of tissues and their pathological changes. Within this perspective, the overall objective of this work includes the proposal, the implementation and the evaluation of a methodology for the analysis of cervical intraepithelial neoplasia (CIN) from histopathological samples through techniques based on Neighbourhood Graphs theory and Complex Networks. The proposed method was evaluated concerning the detection of the presence of lesions in the tissue. The maximum accuracy obtained in the evaluation of the detection of abnormalities was 88%. Since this method is generic, it can be applied to other types of lesions and tissues.