In biology ferment engineering,accurate statistics of the quantity of bacteria is one of the most important subjects. In this paper,the quantity of bacteria which was observed traditionally manuauy can be detected aut...In biology ferment engineering,accurate statistics of the quantity of bacteria is one of the most important subjects. In this paper,the quantity of bacteria which was observed traditionally manuauy can be detected automatically. Image acquisition and processing system is designed to accomplish image preprocessing,image segmentation and statistics of the quantity of bacteria. Segmentation of bacteria images is successfully realized by means of a region-based level set method and then the quantity of bacteria is computed precisely,which plays an important role in optimizing the growth conditions of bacteria.展开更多
Osteosarcoma is primary malignant neoplasms derived from cells of mesenchymal origin, and often has distinct phenotypes at different stages. The location of tumor and reaction zone can be identified by an expert in ma...Osteosarcoma is primary malignant neoplasms derived from cells of mesenchymal origin, and often has distinct phenotypes at different stages. The location of tumor and reaction zone can be identified by an expert in magnetic resonance imaging (MRI), with MRI being one of the choices for evaluating the extent of osteosarcoma. However, it is still a challenge to automatically extract tumor from its surrounding tissues because of their low intensity differences in MRI. We investigated an approach based on Zernike moment and support vector machine (SVM) for osteosarcoma segmentation in T1-weighted image (TIWI). Firstly, the different order moments around each pixel are calculated in small windows. Secondly, the grayscale and the module values of different order moments are used as a texture feature vector which is then used as the training set for SVM. Finally, an SVM classifier is trained based on this set of features to identify the osteosarcoma, and the segmented tumor tissue is rendered in 3D by the ray casting algorithm based on graphics processing unit (GPU). The performance of the method is validated on T1WI, showing that the segmentation method has a high similarity index with the expert's manual segmentation.展开更多
B iolum inescence in aghg is a khd ofem erghg detection technology at cellular, m olecu lar and genetic level. The most popular b io lum m inescence in aghg model is diffusion approxin ation （DA）. However, because ...B iolum inescence in aghg is a khd ofem erghg detection technology at cellular, m olecu lar and genetic level. The most popular b io lum m inescence in aghg model is diffusion approxin ation （DA）. However, because of the ill-posedness of the D A -based hverse problem and the instability of reconstruction algorithm s, the location accuracy of the reconstucted sources is low. Radiative transfer equation （RTE）, which considers the direction of the photon m igration and the effect of absorption and scattering in tissues, can accurately express the transmission ofbiolum hescent photns through the tissues. In this paper, we studied the biolum hescence inaging based on the RTE. 2D sinuiations were performed, and quantitative evaluation was given by the absolute source position error, the relative source area error and the m h in um bound hg box. The resu Its of the experin ent showed that the in aging quality based on R TE was beer than thatone based on D A.展开更多
基金863 Programgrant number:2007AA02Z211+3 种基金Jiangsu Science and Technology Departmentgrant number:BE2008399Education of Jiangsu Provincegrant number:08KJA530002
文摘In biology ferment engineering,accurate statistics of the quantity of bacteria is one of the most important subjects. In this paper,the quantity of bacteria which was observed traditionally manuauy can be detected automatically. Image acquisition and processing system is designed to accomplish image preprocessing,image segmentation and statistics of the quantity of bacteria. Segmentation of bacteria images is successfully realized by means of a region-based level set method and then the quantity of bacteria is computed precisely,which plays an important role in optimizing the growth conditions of bacteria.
文摘Osteosarcoma is primary malignant neoplasms derived from cells of mesenchymal origin, and often has distinct phenotypes at different stages. The location of tumor and reaction zone can be identified by an expert in magnetic resonance imaging (MRI), with MRI being one of the choices for evaluating the extent of osteosarcoma. However, it is still a challenge to automatically extract tumor from its surrounding tissues because of their low intensity differences in MRI. We investigated an approach based on Zernike moment and support vector machine (SVM) for osteosarcoma segmentation in T1-weighted image (TIWI). Firstly, the different order moments around each pixel are calculated in small windows. Secondly, the grayscale and the module values of different order moments are used as a texture feature vector which is then used as the training set for SVM. Finally, an SVM classifier is trained based on this set of features to identify the osteosarcoma, and the segmented tumor tissue is rendered in 3D by the ray casting algorithm based on graphics processing unit (GPU). The performance of the method is validated on T1WI, showing that the segmentation method has a high similarity index with the expert's manual segmentation.
基金The Funding of Jiangsu Innovation Program for Graduate Educationgrant number:SJLX15_0115+1 种基金the Fundamental Research Funds for the Central Universities of Chinagrant number NZ2014101
文摘B iolum inescence in aghg is a khd ofem erghg detection technology at cellular, m olecu lar and genetic level. The most popular b io lum m inescence in aghg model is diffusion approxin ation （DA）. However, because of the ill-posedness of the D A -based hverse problem and the instability of reconstruction algorithm s, the location accuracy of the reconstucted sources is low. Radiative transfer equation （RTE）, which considers the direction of the photon m igration and the effect of absorption and scattering in tissues, can accurately express the transmission ofbiolum hescent photns through the tissues. In this paper, we studied the biolum hescence inaging based on the RTE. 2D sinuiations were performed, and quantitative evaluation was given by the absolute source position error, the relative source area error and the m h in um bound hg box. The resu Its of the experin ent showed that the in aging quality based on R TE was beer than thatone based on D A.
