3D objects can be stored in computer of different describing ways, such as point set, polyline, polygonal surface and Euclidean distance map. Moment invariants of different orders may have the different magnitude. A m...3D objects can be stored in computer of different describing ways, such as point set, polyline, polygonal surface and Euclidean distance map. Moment invariants of different orders may have the different magnitude. A method for normalizing moments of 3D objects is proposed, which can set the values of moments of different orders roughly in the same range and be applied to different 3D data formats universally. Then accurate computation of moments for several objects is presented and experiments show that this kind of normalization is very useful for moment invariants in 3D objects analysis and recognition.展开更多
Electron Tomography （ET） is an important method for studying cell ultrastructure in three-dimensional （3D） space. By combining cryo-electron tomography of frozen-hydrated samples （cryo-ET） and a sub-tomogram ave...Electron Tomography （ET） is an important method for studying cell ultrastructure in three-dimensional （3D） space. By combining cryo-electron tomography of frozen-hydrated samples （cryo-ET） and a sub-tomogram averaging approach, ET has recently reached sub-nanometer resolution, thereby realizing the capability for gaining direct insights into function and mechanism. To obtain a high-resolution 3D ET reconstruction, alignment and geometry determination of the ET tilt series are necessary. However, typical methods for determining geometry require human intervention, which is not only subjective and easily introduces errors, but is also labor intensive for high-throughput tomographic reconstructions. To overcome these problems, we have developed an automatic geometry-determination method, called AutoGDeterm. By taking advantage of the high-contrast re-projections of the Iterative Compressed-sensing Optimized Non-Uniform Fast Fourier Transform （NUFFT） reconstruction （ICON） and a series of numerical analysis methods, AutoGDeterm achieves high-precision fully automated geometry determination. Experimental results on simulated and resin-embedded datasets show that the accuracy of AutoGDeterm is high and comparable to that of the typical ＂manual positioning＂ method. We have made AutoGDeterm available as software, which can be freely downloaded from our website http：//ear.ict.ac.cn.展开更多
基金Supported by National Key Basic Research Program(No.2004CB318006)National Natural Science Foundation of China(Nos.60873164,60573154,60533090,61379082 and 61227802)
文摘3D objects can be stored in computer of different describing ways, such as point set, polyline, polygonal surface and Euclidean distance map. Moment invariants of different orders may have the different magnitude. A method for normalizing moments of 3D objects is proposed, which can set the values of moments of different orders roughly in the same range and be applied to different 3D data formats universally. Then accurate computation of moments for several objects is presented and experiments show that this kind of normalization is very useful for moment invariants in 3D objects analysis and recognition.
基金supported by the National Natural Science Foundation of China (Nos. U1611263, U1611261, 61232001, 61472397, 61502455, and 61672493)the Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase)+1 种基金the Strategic Priority Research Program of Chinese Academy of Sciences (No. XDB08030202)the National Key Research and Development Program of China (No. 2017YFA0504702)
文摘Electron Tomography （ET） is an important method for studying cell ultrastructure in three-dimensional （3D） space. By combining cryo-electron tomography of frozen-hydrated samples （cryo-ET） and a sub-tomogram averaging approach, ET has recently reached sub-nanometer resolution, thereby realizing the capability for gaining direct insights into function and mechanism. To obtain a high-resolution 3D ET reconstruction, alignment and geometry determination of the ET tilt series are necessary. However, typical methods for determining geometry require human intervention, which is not only subjective and easily introduces errors, but is also labor intensive for high-throughput tomographic reconstructions. To overcome these problems, we have developed an automatic geometry-determination method, called AutoGDeterm. By taking advantage of the high-contrast re-projections of the Iterative Compressed-sensing Optimized Non-Uniform Fast Fourier Transform （NUFFT） reconstruction （ICON） and a series of numerical analysis methods, AutoGDeterm achieves high-precision fully automated geometry determination. Experimental results on simulated and resin-embedded datasets show that the accuracy of AutoGDeterm is high and comparable to that of the typical ＂manual positioning＂ method. We have made AutoGDeterm available as software, which can be freely downloaded from our website http：//ear.ict.ac.cn.
