Objective: To investigate the correlation between imaging phenotypes of cervical cancer (CC) and various clinical and histopathological characteristics. Methods: The MRI radiomics features, along with clinical and histopathological characteristics of 164 patients with CC were collected retrospectively from July 2019 to December 2023. All patients were divided into two clusters by consensus clustering based on the radiomics features. The clinical and histopathological characteristics were compared between groups. Results: Clustering analysis based on tumors showed that compared with cluster 1, cluster 2 was associated with a higher correlation with advanced postoperative FIGO stage [IIA or later: 56/92 (60.9%) vs. 22/72 (30.6%), P=0.001], lymph node metastasis [30/92 (32.6%) vs. 9/72 (12.5%), P=0.002], larger tumor diameter in three dimensions (short diameter: 28.38 ± 9.73 mm vs. 16.67 ± 6.32 mm, long diameter: 34.34 ± 9.72 mm vs. 21.02 ± 7.39 mm, height: 29.92 ± 10.61 mm vs. 18.93 ± 8.01 mm, all P<0.001) and deeper stromal invasion [>2/3: 62/92 (67.4%) vs. 26/72 (36.1%), P<0.001]. Clustering analysis based on lymph nodes showed that difference between two clusters in short axis, long axis, short-to-long axis ratio, border, signal and metastasis was not statistically significant. Conclusion: Associations between radiomics features and clinical and histopathological characteristics of patients with CC could be identified by consensus clustering based on multiparametric MRI-based radiomics, suggesting possibilities for preoperative risk stratification.