基于3D＿ResUnet肝脏CT图像分割的临床应用研究

目的:为解决传统肝实质分割方法在阈值分割方面存在的分割精度低的问题。方法:采用AI自动识别算法,通过Unet与Resnet相结合的3D_ResUnet网络对肝脏CT图像进行分割,并对分割结果通过最大联通分量的方法去除杂质,得到较为精确的肝脏区域,实现肝实质自动分割。结果:基于3D_ResUnet的肝脏CT图像分割,其分割的平均Dice为96.12%,高于3D_Unet的分割精度。结论:基于3D_ResUnet的肝脏CT图像分割提高了肝实质分割的精度,实现了无需人工交互的全自动分割,通过应用在肝癌手术计划系统中,为临床医生的肝癌手术规划提供了可视化依据。国家自然科学基金(编号：61327001)~

Development of a quantitative ELISA detection method for Coxsackievirus A group 16 strain(CA16) antigen

目的:建立柯萨奇病毒A组16型(CA16)抗原的双抗体夹心ElISA定量检测方法,用于CA16灭活疫苗的研发和生产过程的抗原定量检测。方法:以CA16中和单抗T26H12为包被抗体、nA14b9为标酶抗体,构建定量检测CA16抗原的双抗体夹心ElISA方法,并对方法的特异性、灵敏度、精密度、准确性、线性和稳定性进行分析。结果:建立了双抗体夹心定量检测CA16抗原的ElISA方法。方法的线性相关系数r2=0.998,线性范围为8~128 ng/Ml,定量限度为8 ng/Ml;变异系数CV80%;与CA16以外的其他样本没有交叉反应。结论:构建的CA16抗原ElISA定量检测方法的各项性能符合定量检测需要,可用于CA16疫苗的研发和生产过程的抗原活性的定量检测。Objective:To develop an a quantitative enzyme linked immunosorbent assay(Q-ELISA) to determine the concentration of Coxsackievirus A Group 16 Strain(CA16) antigen.This method was used to determine CA16 antigen content at each stage of CA16 vaccine developing and manufacturing process.Methods:A double antibody sandwich Q-ELISA was developed to determine concentration of CA16 antigen,which was based on the high-affinity neutralizing monoclonal antibodies T26H12 as capture antibodies,and NA14B9 as HRP-labeled antibody.The performance of reagent were evaluated.Results:The Q-ELISA for CA16 antigen content was successfully developed.The reagent had good performance.The quantitation scope was 8-128 ng/ml,the coefficient correlation was 0.998,the limit of detection was 8 ng/ml,the recovery was between 87% and 113.8%.The stability was up to 80% after reagent was heated for 6 days at 37℃.The variation coefficient was lower than 15%,and thereagent was no reaction with other sample except CA16 antigen.Conclusion:The Q-ELISA for CA16 antigen was developed with good specificity,accuracy,precision and stability.The method can be used to determine CA16 antigen content during development and production of CA16 vaccine