A novel 2-D cosmic ray position detector has been built and studied. It is integrated from a CsI（Na） crystal pixel array, an optical fiber array, an image intensifier and an ICCD camera. The 2-D positions of one cos...A novel 2-D cosmic ray position detector has been built and studied. It is integrated from a CsI（Na） crystal pixel array, an optical fiber array, an image intensifier and an ICCD camera. The 2-D positions of one cosmic ray track is determined by the location of a fired CsI（Na） pixel. The scintillation light of these 1.0× 1.0 mm CsI（Na） pixels is delivered to the image intensifier through fibers. The light information is recorded in the ICCD camera in the form of images, from which the 2-D positions can be reconstructed. The background noise and cosmic ray images have been studied. The study shows that the cosmic ray detection efficiency can reach up to 11.4%, while the false accept rate is less than 1%.展开更多
A method has been developed to establish the crystal position look-up table for positron emission tomography with block detectors. It is based on the principle that the counts in crystal position histogram obey the Ga...A method has been developed to establish the crystal position look-up table for positron emission tomography with block detectors. It is based on the principle that the counts in crystal position histogram obey the Gaussian mixture model (GMM). This method has taken full consideration of the characteristics of the GMM and the detector itself. The experimental results have proved that it is simple, reliable, and universal.展开更多
Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class unifo...Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class uniformity of gray level,a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional(2-D)histogram region oblique division and artificial bee colony(ABC)optimization.Firstly,the definition of reciprocal gray entropy is introduced.Then on the basis of one-dimensional(1-D)method,2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived.To accelerate the progress of searching the optimal threshold,the recently proposed ABC optimization algorithm is adopted.The proposed method not only avoids the undefined value points in Shannon entropy,but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level.A large number of experimental results show that,compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization(NCPSO),the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.展开更多
目的:探讨DWI对Her-2阳性过表达型乳腺癌和Basal-Like基底样型乳腺癌的鉴别诊断价值。方法 :收集经病理证实的74例乳腺癌,其中Her-2阳性过表达型43例,Basal-Like基底样31例,获取其DWI图像,后经GE AW 4.6工作站和Matlab软件分别获取病灶...目的:探讨DWI对Her-2阳性过表达型乳腺癌和Basal-Like基底样型乳腺癌的鉴别诊断价值。方法 :收集经病理证实的74例乳腺癌,其中Her-2阳性过表达型43例,Basal-Like基底样31例,获取其DWI图像,后经GE AW 4.6工作站和Matlab软件分别获取病灶的ADC参数及直方图参数。采用Mann-Whitney检验及ROC曲线评判ADC参数和直方图参数对Her-2阳性过表达型乳腺癌和Basal-Like基底样型乳腺癌的鉴别诊断价值。此外,尝试基于DWI图像的直方图参数建立Logistic回归模型实现对两类乳腺癌的鉴别。结果:ADC值在2类乳腺癌中差异有统计学意义(P<0.01),但ROC曲线分析显示ADC值鉴别2类乳腺癌的敏感度和特异度较低;在所有的直方图参数中,DWI图像灰度值的最小值对2类乳腺癌的鉴别诊断能力最高(P<0.01,AUC=0.87);Logistic回归模型对2类乳腺癌的鉴别准确率为83.78%,预测概率ROC曲线下面积为0.88。结论:ADC值可实现对Her-2阳性过表达型和Basal-Like基底样型乳腺癌的鉴别诊断。DWI图像结合Logistic回归分析对2类乳腺癌的鉴别具有较高的敏感度和特异度。展开更多
The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circ...The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circumstances. Thus, a threshold selection method is proposed on the basis of area difference between background and object and intra-class variance. The threshold selection formulae based on one-dimensional (1-D) histogram, two-dimensional (2-D) histogram vertical segmentation and 2-D histogram oblique segmentation are given. A fast recursive algorithm of threshold selection in 2-D histogram oblique segmentation is derived. The segmented images and processing time of the proposed method are given in experiments. It is compared with some fast algorithms, such as Otsu, maximum entropy and Fisher threshold selection methods. The experimental results show that the proposed method can effectively segment the small object images and has better anti-noise property.展开更多
文摘A novel 2-D cosmic ray position detector has been built and studied. It is integrated from a CsI（Na） crystal pixel array, an optical fiber array, an image intensifier and an ICCD camera. The 2-D positions of one cosmic ray track is determined by the location of a fired CsI（Na） pixel. The scintillation light of these 1.0× 1.0 mm CsI（Na） pixels is delivered to the image intensifier through fibers. The light information is recorded in the ICCD camera in the form of images, from which the 2-D positions can be reconstructed. The background noise and cosmic ray images have been studied. The study shows that the cosmic ray detection efficiency can reach up to 11.4%, while the false accept rate is less than 1%.
基金Supported by the National High-Tech Research and Development Program of China ("863") (Grant No. 2006AA020803)
文摘A method has been developed to establish the crystal position look-up table for positron emission tomography with block detectors. It is based on the principle that the counts in crystal position histogram obey the Gaussian mixture model (GMM). This method has taken full consideration of the characteristics of the GMM and the detector itself. The experimental results have proved that it is simple, reliable, and universal.
基金Supported by the CRSRI Open Research Program(CKWV2013225/KY)the Priority Academic Program Development of Jiangsu Higher Education Institution+2 种基金the Open Project Foundation of Key Laboratory of the Yellow River Sediment of Ministry of Water Resource(2014006)the State Key Lab of Urban Water Resource and Environment(HIT)(ES201409)the Open Project Program of State Key Laboratory of Food Science and Technology,Jiangnan University(SKLF-KF-201310)
文摘Since the logarithmic form of Shannon entropy has the drawback of undefined value at zero points,and most existing threshold selection methods only depend on the probability information,ignoring the within-class uniformity of gray level,a method of reciprocal gray entropy threshold selection is proposed based on two-dimensional(2-D)histogram region oblique division and artificial bee colony(ABC)optimization.Firstly,the definition of reciprocal gray entropy is introduced.Then on the basis of one-dimensional(1-D)method,2-D threshold selection criterion function based on reciprocal gray entropy with histogram oblique division is derived.To accelerate the progress of searching the optimal threshold,the recently proposed ABC optimization algorithm is adopted.The proposed method not only avoids the undefined value points in Shannon entropy,but also achieves high accuracy and anti-noise performance due to reasonable 2-D histogram region division and the consideration of within-class uniformity of gray level.A large number of experimental results show that,compared with the maximum Shannon entropy method with 2-D histogram oblique division and the reciprocal entropy method with 2-D histogram oblique division based on niche chaotic mutation particle swarm optimization(NCPSO),the proposed method can achieve better segmentation results and can satisfy the requirement of real-time processing.
文摘目的:探讨DWI对Her-2阳性过表达型乳腺癌和Basal-Like基底样型乳腺癌的鉴别诊断价值。方法 :收集经病理证实的74例乳腺癌,其中Her-2阳性过表达型43例,Basal-Like基底样31例,获取其DWI图像,后经GE AW 4.6工作站和Matlab软件分别获取病灶的ADC参数及直方图参数。采用Mann-Whitney检验及ROC曲线评判ADC参数和直方图参数对Her-2阳性过表达型乳腺癌和Basal-Like基底样型乳腺癌的鉴别诊断价值。此外,尝试基于DWI图像的直方图参数建立Logistic回归模型实现对两类乳腺癌的鉴别。结果:ADC值在2类乳腺癌中差异有统计学意义(P<0.01),但ROC曲线分析显示ADC值鉴别2类乳腺癌的敏感度和特异度较低;在所有的直方图参数中,DWI图像灰度值的最小值对2类乳腺癌的鉴别诊断能力最高(P<0.01,AUC=0.87);Logistic回归模型对2类乳腺癌的鉴别准确率为83.78%,预测概率ROC曲线下面积为0.88。结论:ADC值可实现对Her-2阳性过表达型和Basal-Like基底样型乳腺癌的鉴别诊断。DWI图像结合Logistic回归分析对2类乳腺癌的鉴别具有较高的敏感度和特异度。
基金Sponsored by The National Natural Science Foundation of China(60872065)Science and Technology on Electro-optic Control Laboratory and Aviation Science Foundation(20105152026)State Key Laboratory Open Fund of Novel Software Technology,Nanjing University(KFKT2010B17)
文摘The image segmentation difficulties of small objects which are much smaller than their background often occur in target detection and recognition. The existing threshold segmentation methods almost fail under the circumstances. Thus, a threshold selection method is proposed on the basis of area difference between background and object and intra-class variance. The threshold selection formulae based on one-dimensional (1-D) histogram, two-dimensional (2-D) histogram vertical segmentation and 2-D histogram oblique segmentation are given. A fast recursive algorithm of threshold selection in 2-D histogram oblique segmentation is derived. The segmented images and processing time of the proposed method are given in experiments. It is compared with some fast algorithms, such as Otsu, maximum entropy and Fisher threshold selection methods. The experimental results show that the proposed method can effectively segment the small object images and has better anti-noise property.
