A homological multi-information image fusion method was introduced for recognition of the gastric tumor pathological tissue images.The main purpose is that fewer procedures are used to provide more information and the...A homological multi-information image fusion method was introduced for recognition of the gastric tumor pathological tissue images.The main purpose is that fewer procedures are used to provide more information and the result images could be easier to be understood than any other methods.First,multi-scale wavelet transform was used to extract edge feature,and then watershed morphology was used to form multi-threshold grayscale contours.The research laid emphasis upon the homological tissue image fusion based on extended Bayesian algorithm,which fusion result images of linear weighted algorithm was used to compare with the ones of extended Bayesian algorithm.The final fusion images are shown in Fig 5.The final image evaluation was made by information entropy,information correlativity and statistics methods.It is indicated that this method has more advantages for clinical application.展开更多
目的以脉冲场凝胶电泳(pulsed field gel electrophoresis,PFGE)为金标准,评价基质辅助激光解吸电离飞行时间质谱(matrix-assisted laser desorption/ionization time-of-flight mass spectrometry,MALDI-TOF MS)在多重耐药铜绿假单胞菌...目的以脉冲场凝胶电泳(pulsed field gel electrophoresis,PFGE)为金标准,评价基质辅助激光解吸电离飞行时间质谱(matrix-assisted laser desorption/ionization time-of-flight mass spectrometry,MALDI-TOF MS)在多重耐药铜绿假单胞菌(multi-drug resistant Pseudomonas aeruginosa,MDR-PA)同源性分析中应用的可行性。方法收集陆军军医大学第三附属医院2017年1-12月重症监护病房住院患者分离的20株MDR-PA非重复菌株,利用VITEK MS SARAMIS软件对MDR-PA蛋白图谱进行聚类分析,同时对其进行PFGE同源性分析,并将两种方法所得的分型结果进行对比分析。结果 MALDITOF MS同源性分析结果与PFGE同源性分析结果比较显示,20株MDR-PA通过MALDI-TOF MS聚类分析将其分为三大簇(Ⅰ型13株,Ⅱ型6株,Ⅲ型1株),而依据PFGE分型结果则将其分为6种亚型(A型2株,B型3株,C型4株,D型3株,E型7株,F型1株),其中有C型和E型中具有相同基因型菌株间,其MALDI-TOF MS亲缘性关系也较近,而其余4种亚型菌株间亲缘性比较,发现PFGE分型结果与MALDI-TOF MS聚类分析结果不完全相符。结论与PFGE同源性分析相比,MALDI-TOF MS同源性分析结果一致性不稳定,具有一定局限性,尚不能取代PFGE同源性分析。展开更多
基金Supported by the National Science Foundation of China(No.30370403 )
文摘A homological multi-information image fusion method was introduced for recognition of the gastric tumor pathological tissue images.The main purpose is that fewer procedures are used to provide more information and the result images could be easier to be understood than any other methods.First,multi-scale wavelet transform was used to extract edge feature,and then watershed morphology was used to form multi-threshold grayscale contours.The research laid emphasis upon the homological tissue image fusion based on extended Bayesian algorithm,which fusion result images of linear weighted algorithm was used to compare with the ones of extended Bayesian algorithm.The final fusion images are shown in Fig 5.The final image evaluation was made by information entropy,information correlativity and statistics methods.It is indicated that this method has more advantages for clinical application.
