RESUMO
PURPOSE: To propose a fast detection method for prostate cancer abnormal cells based on deep learning. The purpose of this method is to quickly and accurately locate and identify abnormal cells, so as to improve the efficiency of prostate precancerous screening and promote the application and popularization of prostate cancer cell assisted screening technology. METHOD: The method includes two stages: preliminary screening of abnormal cell images and accurate identification of abnormal cells. In the preliminary screening stage of abnormal cell images, ResNet50 model is used as the image classification network to judge whether the local area contains cell clusters. In the another stage, YoloV5 model is used as the target detection network to locate and recognize abnormal cells in the image containing cell clusters. RESULTS: This detection method aims at the pathological cell images obtained by the membrane method. And the double stage models proposed in this paper are compared with the single stage model method using only the target detection model. The results show that through the image classification network based on deep learning, we can first judge whether there are abnormal cells in the local area. If there are abnormal cells, we can further use the target detection method based on candidate box for analysis, which can reduce the reasoning time by 50% and improve the efficiency of abnormal cell detection under the condition of losing a small amount of accuracy and slightly increasing the complexity of the model. CONCLUSION: This study proposes a fast detection method for prostate cancer abnormal cells based on deep learning, which can greatly shorten the reasoning time and improve the detection speed. It is able to improve the efficiency of prostate precancerous screening.
Assuntos
Lesões Pré-Cancerosas , Neoplasias da Próstata , Masculino , Humanos , Próstata/patologia , Neoplasias da Próstata/diagnóstico por imagem , Neoplasias da Próstata/patologiaRESUMO
Breast cancer (BC) is a common malignancy among women and the leading cause of female cancer mortality worldwide. In recent years, increasing evidence has shown that long noncoding RNAs (lncRNAs) can act as competing endogenous RNAs (ceRNAs) in human cancer and that they are involved in many biological processes, including proliferation, migration, apoptosis and invasion. In the present study, the biological function and molecular mechanism of ataxin 8 opposite strand (ATXN8OS) in BC tissue and cell lines were investigated. It was found that ATXN8OS was markedly upregulated in BC tissue and cell lines, and that its level of overexpression was inversely linked with the overall survival rate of patients with BC. Knockdown of ATXN8OS inhibited proliferation, viability and invasion in the human MCF7 and MDAMB231 BC cell lines. In addition, microRNA204 (miR204) was negatively associated with the expression of ATXN8OS in BC tissues and cell lines. A luciferase assay demonstrated a direct binding site for miR204 within ATXN8OS, and inhibition of miR204 stimulated the tumourpromoting effect of ATXN8OS on BC cells. In conclusion, the present study suggested that ATXN8OS acts as a tumour promoter by sequestering miR204 during the development of BC, therefore providing a mechanistic insight which may facilitate the diagnosis and treatment of BC.