AUTHOR=Huang Wei , Sun Shasha , Yu Zhengyu , Lu Shanshan , Feng Hao TITLE=Chronic Cervicitis and Cervical Cancer Detection Based on Deep Learning of Colposcopy Images Toward Translational Pharmacology JOURNAL=Frontiers in Pharmacology VOLUME=Volume 13 - 2022 YEAR=2022 URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2022.911962 DOI=10.3389/fphar.2022.911962 ISSN=1663-9812 ABSTRACT=With the rapid development of deep learning, automatic image recognition is widely used in medical development. In this study, a deep learning convolutional neural network model was developed to recognize and classify chronic cervicitis and cervical cancer. A total of 10012 colposcopy images of 1081 patients from Hunan Provincial people’s hospital in China were recorded. Five different colposcopy image features of cervix include chronic cervicitis, intraepithelial lesions, cancer, polypus and free hyperplastic squamous epithelial tissue were extracted to be applied in our deep learning network convolutional neural network model. However, result showed a low accuracy (42.16%) due to computer misrecognition of chronic inflammation, intraepithelial lesions and free hyperplastic squamous epithelial tissue with high similarity. To optimize this model, we selected two significant features images - chronic cervicitis and cervical cancer to input into deep learning network. The result indicates high accuracy and robustness with the accuracy of 95.19%, which can be applied to detect whether patient has chronic cervicitis or cervical cancer base on patient’s colposcopy images.