Objective To observe the value of preoperative CT radiomics models for predicting composition of in vivo urinary calculi.Methods Totally 543 urolithiasis patients were retrospectively enrolled and divided into calcium...Objective To observe the value of preoperative CT radiomics models for predicting composition of in vivo urinary calculi.Methods Totally 543 urolithiasis patients were retrospectively enrolled and divided into calcium oxalate monohydrate stone group(group A,n=373),anhydrous uric acid stone group(group B,n=86),carbonate apatite group(group C,n=30),ammonium urate stone group(group D,n=28)and ammonium magnesium phosphate hexahydrate stone group(group E,n=26)according to the composition of calculi,also divided into training set and test set at the ratio of 7∶3.Radiomics features were extracted and screened based on plain CT images of urinary system.Five binary task models(model A—E corresponding to group A—E)and a quinary task model were constructed using least absolute shrinkage and selection operator algorithm for predicting the composition of calculi in vivo.Then receiver operating characteristic curves were drawn,and the area under the curves(AUC)were calculated to evaluate the predictive efficacy of binary task models,while the accuracy,precision,recall and F1 score were used to evaluate the predictive efficacy of the quinary task model.Results All binary task models had good efficacy for predicting the composition of urinary calculi in vivo,with AUC of 0.860—0.948 in training set and of 0.856—0.933 in test set.The accuracy,precision,recall and F1 score of the quinary task model for predicting the composition of in vivo urinary calculi was 82.25%,83.79%,46.23%and 0.596 in training set,respectively,while was 80.63%,75.26%,43.48%and 0.551 in test set,respectively.Conclusion Binary task radiomics models based on preoperative plain CT had good efficacy for predicting the composition of in vivo urinary calculi,while the quinary task radiomics model had high accuracy but relatively poor stability.展开更多
Artificial bone with porous structure is crucial for tissue scaffold and clinic implants.Scaffold provides structure support for cells and guides tissues regeneration for final tissue structure.A computational aided p...Artificial bone with porous structure is crucial for tissue scaffold and clinic implants.Scaffold provides structure support for cells and guides tissues regeneration for final tissue structure.A computational aided process of porous bone modeling was developed which described the design and fabrication of tissue scaffolds by considering intricate architecture,porosity and pore size.To simulate intricate bone structure,different constructive units were presented.In modeling process,bone contour was gotten from computed tomography(CT)images and was divided into two levels.Each level was represented by relatively reconstructive process.Pore size distribution was controlled by using mesh generation.The whole hexahedral mesh was reduced by unit structure,when a 3D mesh with various hexahedral elements was provided.The simulation results show that constructive structure of porous scaffold can meet the needs of clinic implants in accurate and controlled way.展开更多
The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this wor...The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.展开更多
Micro computed tomography (Micro-CT) was applied to obtain three-dimensional images of the microstructure of cement paste (water-to-cement mass ratio of 0.5) at different ages. By using the Amira software, component p...Micro computed tomography (Micro-CT) was applied to obtain three-dimensional images of the microstructure of cement paste (water-to-cement mass ratio of 0.5) at different ages. By using the Amira software, component phases of the cement paste such as pores, hydration products, and unhydrated clinker particles were segmented from each other based on their 3D image grey levels; their relative contents were also calculated with the software, and the data are 61.2%, 0% and 38.8% at the beginning of hydration and 11.8%, 78.5% and 9.7% at 28 d age, respectively. The hydration degree of cement paste at different ages was compared with the experimental data acquired by loss on ignition (LOI) tests. The results show that the calculated and measured data reasonably agree with each other, which indicates that micro-CT is a useful and reliable approach to characterize the micro structure evolution of hydrating cement paste.展开更多
文摘Objective To observe the value of preoperative CT radiomics models for predicting composition of in vivo urinary calculi.Methods Totally 543 urolithiasis patients were retrospectively enrolled and divided into calcium oxalate monohydrate stone group(group A,n=373),anhydrous uric acid stone group(group B,n=86),carbonate apatite group(group C,n=30),ammonium urate stone group(group D,n=28)and ammonium magnesium phosphate hexahydrate stone group(group E,n=26)according to the composition of calculi,also divided into training set and test set at the ratio of 7∶3.Radiomics features were extracted and screened based on plain CT images of urinary system.Five binary task models(model A—E corresponding to group A—E)and a quinary task model were constructed using least absolute shrinkage and selection operator algorithm for predicting the composition of calculi in vivo.Then receiver operating characteristic curves were drawn,and the area under the curves(AUC)were calculated to evaluate the predictive efficacy of binary task models,while the accuracy,precision,recall and F1 score were used to evaluate the predictive efficacy of the quinary task model.Results All binary task models had good efficacy for predicting the composition of urinary calculi in vivo,with AUC of 0.860—0.948 in training set and of 0.856—0.933 in test set.The accuracy,precision,recall and F1 score of the quinary task model for predicting the composition of in vivo urinary calculi was 82.25%,83.79%,46.23%and 0.596 in training set,respectively,while was 80.63%,75.26%,43.48%and 0.551 in test set,respectively.Conclusion Binary task radiomics models based on preoperative plain CT had good efficacy for predicting the composition of in vivo urinary calculi,while the quinary task radiomics model had high accuracy but relatively poor stability.
基金Project(2011DFB70230)supported by State International Cooperation Program of ChinaProject(N110403003)supported by Basic Research Foundation of Education Ministry of China
文摘Artificial bone with porous structure is crucial for tissue scaffold and clinic implants.Scaffold provides structure support for cells and guides tissues regeneration for final tissue structure.A computational aided process of porous bone modeling was developed which described the design and fabrication of tissue scaffolds by considering intricate architecture,porosity and pore size.To simulate intricate bone structure,different constructive units were presented.In modeling process,bone contour was gotten from computed tomography(CT)images and was divided into two levels.Each level was represented by relatively reconstructive process.Pore size distribution was controlled by using mesh generation.The whole hexahedral mesh was reduced by unit structure,when a 3D mesh with various hexahedral elements was provided.The simulation results show that constructive structure of porous scaffold can meet the needs of clinic implants in accurate and controlled way.
基金Projects(61573144,61773165,61673175,61174040)supported by the National Natural Science Foundation of ChinaProject(222201717006)supported by the Fundamental Research Funds for the Central Universities,China
文摘The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.
基金Project(2009CB623201) supported by the National Basic Research Program of ChinaProjects(50902106, 51272193) supported by the National Natural Science Foundation of ChinaProject(NCET-10-0660) supported by New Century Excellent Talents in Universities of China
文摘Micro computed tomography (Micro-CT) was applied to obtain three-dimensional images of the microstructure of cement paste (water-to-cement mass ratio of 0.5) at different ages. By using the Amira software, component phases of the cement paste such as pores, hydration products, and unhydrated clinker particles were segmented from each other based on their 3D image grey levels; their relative contents were also calculated with the software, and the data are 61.2%, 0% and 38.8% at the beginning of hydration and 11.8%, 78.5% and 9.7% at 28 d age, respectively. The hydration degree of cement paste at different ages was compared with the experimental data acquired by loss on ignition (LOI) tests. The results show that the calculated and measured data reasonably agree with each other, which indicates that micro-CT is a useful and reliable approach to characterize the micro structure evolution of hydrating cement paste.
