Computed tomography has made significant advances since its intro-duction in the early 1970s,where researchers have mainly focused on the quality of image reconstruction in the early stage.However,radiation exposure p...Computed tomography has made significant advances since its intro-duction in the early 1970s,where researchers have mainly focused on the quality of image reconstruction in the early stage.However,radiation exposure poses a health risk,prompting the demand of the lowest possible dose when carrying out CT examinations.To acquire high-quality reconstruction images with low dose radiation,CT reconstruction techniques have evolved from conventional reconstruction such as analytical and iterative reconstruction,to reconstruction methods based on artificial intelligence(AI).All these efforts are devoted to con-structing high-quality images using only low doses with fast reconstruction speed.In particular,conventional reconstruction methods usually optimize one aspect,while AI-based reconstruction has finally managed to attain all goals in one shot.However,there are limitations such as the requirements on large datasets,unstable performance,and weak generalizability in AI-based reconstruction methods.This work presents the review and discussion on the classification,the commercial use,the advantages,and the limitations of AI-based image reconstruction methods in CT.展开更多
Optical molecular tomography(OMT)is an imaging modality which uses an optical signal,especially near-infrared light,to reconstruct the three-dimensional information of the light source in biological tissue.With the ad...Optical molecular tomography(OMT)is an imaging modality which uses an optical signal,especially near-infrared light,to reconstruct the three-dimensional information of the light source in biological tissue.With the advantages of being low-cost,noninvasive and having high sensitivity,OMT has been applied in preclinical and clinical research.However,due to its serious ill-posedness and illcondition,the solution of OMT requires heavy data analysis and the reconstruction quality is limited.Recently,the artificial intelligence(commonly known as AI)-based methods have been proposed to provide a different tool to solve the OMT problem.In this paper,we review the progress on OMT algorithms,from conventional methods to AI-based methods,and we also give a prospective towards future developments in this domain.展开更多
Hepatocellular carcinoma(HCC)constitutes the fifth most frequent malignancy worldwide and the third most frequent cause of cancer-related deaths.Currently,treatment selection is based on the stage of the disease.Emerg...Hepatocellular carcinoma(HCC)constitutes the fifth most frequent malignancy worldwide and the third most frequent cause of cancer-related deaths.Currently,treatment selection is based on the stage of the disease.Emerging fields such as three-dimensional(3D)printing,3D bioprinting,artificial intelligence(AI),and machine learning(ML)could lead to evidence-based,individualized management of HCC.In this review,we comprehensively report the current applications of 3D printing,3D bioprinting,and AI/ML-based models in HCC management;we outline the significant challenges to the broad use of these novel technologies in the clinical setting with the goal of identifying means to overcome them,and finally,we discuss the opportunities that arise from these applications.Notably,regarding 3D printing and bioprinting-related challenges,we elaborate on cost and cost-effectiveness,cell sourcing,cell viability,safety,accessibility,regulation,and legal and ethical concerns.Similarly,regarding AI/ML-related challenges,we elaborate on intellectual property,liability,intrinsic biases,data protection,cybersecurity,ethical challenges,and transparency.Our findings show that AI and 3D printing applications in HCC management and healthcare,in general,are steadily expanding;thus,these technologies will be integrated into the clinical setting sooner or later.Therefore,we believe that physicians need to become familiar with these technologies and prepare to engage with them constructively.展开更多
In this editorial,we review recent progress on the applications of artificial intelligence(AI)in image reconstruction for biomedical imaging.Because it abandons prior information of traditional artificial design and a...In this editorial,we review recent progress on the applications of artificial intelligence(AI)in image reconstruction for biomedical imaging.Because it abandons prior information of traditional artificial design and adopts a completely data-driven mode to obtain deeper prior information via learning,AI technology plays an increasingly important role in biomedical image reconstruction.The combination of AI technology and the biomedical image reconstruction method has become a hotspot in the field.Favoring AI,the performance of biomedical image reconstruction has been improved in terms of accuracy,resolution,imaging speed,etc.We specifically focus on how to use AI technology to improve the performance of biomedical image reconstruction,and propose possible future directions in this field.展开更多
Prosthodontics,deals in the restoration and replacement of missing and structurally compromised teeth,this field has been remarkably transformed in the last two decades.Through the integration of digital imaging and t...Prosthodontics,deals in the restoration and replacement of missing and structurally compromised teeth,this field has been remarkably transformed in the last two decades.Through the integration of digital imaging and threedimensional printing,prosthodontics has evolved to provide more durable,precise,and patient-centric outcome.However,as we stand at the convergence of technology and healthcare,a new era is emerging,one that holds immense promise for the field and that is artificial intelligence(AI).In this paper,we explored the fascinating challenges and prospects associated with the future of prosthodontics in the era of AI.展开更多
The creation of three-dimensional models from an unorganized set of points is an active research area in computer graphics.One of the purposes of this study is to explore the 3D reconstruction of a cube-type artificia...The creation of three-dimensional models from an unorganized set of points is an active research area in computer graphics.One of the purposes of this study is to explore the 3D reconstruction of a cube-type artificial reef(CTAR)set by linear structured light and binocular stereo vision technology in an underwater environment.The experimental setup is composed of two ca-meras in a stereo vision configuration.The alpha shapes method can be used to construct a surface that most closely reflects the arti-ficial reef set described by the points.A parameter study is conducted to assess the scales of the set(i.e.,usable volume,surface area,projected area,height,and base diameter)on the basis of 3D reconstruction.Experimental results show that the quality of 3D recon-struction in an underwater environment is acceptable for estimating the scale size of the CTAR set.According to the measurement of the scale sizing of the CTAR set,the relationships between the parameters of the CTAR set and the number of CTAR modules were determined.Moreover,the usable volume of the CTAR set can be estimated depending on the basis of the number of CTAR modules.展开更多
Artificial intelligence(AI)is the study of algorithms that enable machines to analyze and execute cognitive activities including problem solving,object and word recognition,reduce the inevitable errors to improve the ...Artificial intelligence(AI)is the study of algorithms that enable machines to analyze and execute cognitive activities including problem solving,object and word recognition,reduce the inevitable errors to improve the diagnostic accuracy,and decision-making.Hepatobiliary procedures are technically complex and the use of AI in perioperative management can improve patient outcomes as discussed below.Three-dimensional(3D)reconstruction of images obtained via ultrasound,computed tomography scan or magnetic resonance imaging,can help surgeons better visualize the surgical sites with added depth perception.Preoperative 3D planning is associated with lesser operative time and intraoperative complications.Also,a more accurate assessment is noted,which leads to fewer operative complications.Images can be converted into physical models with 3D printing technology,which can be of educational value to students and trainees.3D images can be combined to provide 3D visualization,which is used for preoperative navigation,allowing for more precise localization of tumors and vessels.Nevertheless,AI enables surgeons to provide better,personalized care for each patient.展开更多
基金This work is supported by the National Key Research and Development Program of China(2020YFC2003400)Qiang Ni’s work was funded by the UK EPSRC project under grant number EP/K011693/1.
文摘Computed tomography has made significant advances since its intro-duction in the early 1970s,where researchers have mainly focused on the quality of image reconstruction in the early stage.However,radiation exposure poses a health risk,prompting the demand of the lowest possible dose when carrying out CT examinations.To acquire high-quality reconstruction images with low dose radiation,CT reconstruction techniques have evolved from conventional reconstruction such as analytical and iterative reconstruction,to reconstruction methods based on artificial intelligence(AI).All these efforts are devoted to con-structing high-quality images using only low doses with fast reconstruction speed.In particular,conventional reconstruction methods usually optimize one aspect,while AI-based reconstruction has finally managed to attain all goals in one shot.However,there are limitations such as the requirements on large datasets,unstable performance,and weak generalizability in AI-based reconstruction methods.This work presents the review and discussion on the classification,the commercial use,the advantages,and the limitations of AI-based image reconstruction methods in CT.
基金Supported by the National Natural Science Foundation of China,No.61701403the Project Funded by China Post-doctoral Science Foundation,No.2018M643719+2 种基金the Young Talent Support Program of the Shaanxi Association for Science and Technology,No.20190107the Scientific Research Program Funded by Shaanxi Provincial Education Department,No.18JK0767and the Natural Science Research Plan Program in Shaanxi Province of China,No.2017JQ6006.
文摘Optical molecular tomography(OMT)is an imaging modality which uses an optical signal,especially near-infrared light,to reconstruct the three-dimensional information of the light source in biological tissue.With the advantages of being low-cost,noninvasive and having high sensitivity,OMT has been applied in preclinical and clinical research.However,due to its serious ill-posedness and illcondition,the solution of OMT requires heavy data analysis and the reconstruction quality is limited.Recently,the artificial intelligence(commonly known as AI)-based methods have been proposed to provide a different tool to solve the OMT problem.In this paper,we review the progress on OMT algorithms,from conventional methods to AI-based methods,and we also give a prospective towards future developments in this domain.
文摘Hepatocellular carcinoma(HCC)constitutes the fifth most frequent malignancy worldwide and the third most frequent cause of cancer-related deaths.Currently,treatment selection is based on the stage of the disease.Emerging fields such as three-dimensional(3D)printing,3D bioprinting,artificial intelligence(AI),and machine learning(ML)could lead to evidence-based,individualized management of HCC.In this review,we comprehensively report the current applications of 3D printing,3D bioprinting,and AI/ML-based models in HCC management;we outline the significant challenges to the broad use of these novel technologies in the clinical setting with the goal of identifying means to overcome them,and finally,we discuss the opportunities that arise from these applications.Notably,regarding 3D printing and bioprinting-related challenges,we elaborate on cost and cost-effectiveness,cell sourcing,cell viability,safety,accessibility,regulation,and legal and ethical concerns.Similarly,regarding AI/ML-related challenges,we elaborate on intellectual property,liability,intrinsic biases,data protection,cybersecurity,ethical challenges,and transparency.Our findings show that AI and 3D printing applications in HCC management and healthcare,in general,are steadily expanding;thus,these technologies will be integrated into the clinical setting sooner or later.Therefore,we believe that physicians need to become familiar with these technologies and prepare to engage with them constructively.
基金Supported by The National Key R&D Program of China,No.2018YFC0910600the National Natural Science Foundation of China No.81627807 and 11727813+2 种基金Shaanxi Science Funds for Distinguished Young Scholars,No.2020JC-27the Fok Ying Tung Education Foundation,No.161104and Program for the Young Topnotch Talent of Shaanxi Province.
文摘In this editorial,we review recent progress on the applications of artificial intelligence(AI)in image reconstruction for biomedical imaging.Because it abandons prior information of traditional artificial design and adopts a completely data-driven mode to obtain deeper prior information via learning,AI technology plays an increasingly important role in biomedical image reconstruction.The combination of AI technology and the biomedical image reconstruction method has become a hotspot in the field.Favoring AI,the performance of biomedical image reconstruction has been improved in terms of accuracy,resolution,imaging speed,etc.We specifically focus on how to use AI technology to improve the performance of biomedical image reconstruction,and propose possible future directions in this field.
文摘Prosthodontics,deals in the restoration and replacement of missing and structurally compromised teeth,this field has been remarkably transformed in the last two decades.Through the integration of digital imaging and threedimensional printing,prosthodontics has evolved to provide more durable,precise,and patient-centric outcome.However,as we stand at the convergence of technology and healthcare,a new era is emerging,one that holds immense promise for the field and that is artificial intelligence(AI).In this paper,we explored the fascinating challenges and prospects associated with the future of prosthodontics in the era of AI.
基金This research was supported by the National Key R&D Program of China(No.2019YFD0901302)the National Natural Science Foundation of China(No.31802349).
文摘The creation of three-dimensional models from an unorganized set of points is an active research area in computer graphics.One of the purposes of this study is to explore the 3D reconstruction of a cube-type artificial reef(CTAR)set by linear structured light and binocular stereo vision technology in an underwater environment.The experimental setup is composed of two ca-meras in a stereo vision configuration.The alpha shapes method can be used to construct a surface that most closely reflects the arti-ficial reef set described by the points.A parameter study is conducted to assess the scales of the set(i.e.,usable volume,surface area,projected area,height,and base diameter)on the basis of 3D reconstruction.Experimental results show that the quality of 3D recon-struction in an underwater environment is acceptable for estimating the scale size of the CTAR set.According to the measurement of the scale sizing of the CTAR set,the relationships between the parameters of the CTAR set and the number of CTAR modules were determined.Moreover,the usable volume of the CTAR set can be estimated depending on the basis of the number of CTAR modules.
文摘Artificial intelligence(AI)is the study of algorithms that enable machines to analyze and execute cognitive activities including problem solving,object and word recognition,reduce the inevitable errors to improve the diagnostic accuracy,and decision-making.Hepatobiliary procedures are technically complex and the use of AI in perioperative management can improve patient outcomes as discussed below.Three-dimensional(3D)reconstruction of images obtained via ultrasound,computed tomography scan or magnetic resonance imaging,can help surgeons better visualize the surgical sites with added depth perception.Preoperative 3D planning is associated with lesser operative time and intraoperative complications.Also,a more accurate assessment is noted,which leads to fewer operative complications.Images can be converted into physical models with 3D printing technology,which can be of educational value to students and trainees.3D images can be combined to provide 3D visualization,which is used for preoperative navigation,allowing for more precise localization of tumors and vessels.Nevertheless,AI enables surgeons to provide better,personalized care for each patient.
