Universal lesion detection(ULD)methods for computed tomography(CT)images play a vital role in the modern clinical medicine and intelligent automation.It is well known that single 2D CT slices lack spatial-temporal cha...Universal lesion detection(ULD)methods for computed tomography(CT)images play a vital role in the modern clinical medicine and intelligent automation.It is well known that single 2D CT slices lack spatial-temporal characteristics and contextual information compared to 3D CT blocks.However,3D CT blocks necessitate significantly higher hardware resources during the learning phase.Therefore,efficiently exploiting temporal correlation and spatial-temporal features of 2D CT slices is crucial for ULD tasks.In this paper,we propose a ULD network with the enhanced temporal correlation for this purpose,named TCE-Net.The designed TCE module is applied to enrich the discriminate feature representation of multiple sequential CT slices.Besides,we employ multi-scale feature maps to facilitate the localization and detection of lesions in various sizes.Extensive experiments are conducted on the DeepLesion benchmark demonstrate that thismethod achieves 66.84%and 78.18%for FS@0.5 and FS@1.0,respectively,outperforming compared state-of-the-art methods.展开更多
We examine how noise interacts with encoding mechanisms of neuronal stimulus in a cold receptor. From ISI series and bifurcation diagrams it is shown that there are considerable differences in interval distributions a...We examine how noise interacts with encoding mechanisms of neuronal stimulus in a cold receptor. From ISI series and bifurcation diagrams it is shown that there are considerable differences in interval distributions and impulse patterns caused by purely deterministic simulations and noisy simulations. The ISI-distance can be used as an effective and powerful way to measure the noise effects on spike trains of the cold receptor quantitatively. It is also found that spike trains observed in cold receptors can be more strongly affected by noise for low temperatures than for high temperatures in some aspects; meanwhile, the spike train has greater variability with increasing noise intensity.展开更多
We study the dynamics of tumor cell growth with time-delayed feedback driven by multiplicative noise in an asymmetrical bistable potential well. For a small delay time, the analytical solutions of the probability dist...We study the dynamics of tumor cell growth with time-delayed feedback driven by multiplicative noise in an asymmetrical bistable potential well. For a small delay time, the analytical solutions of the probability distribution and the first passage time show that, with the increasing delay time, the peak of the probability distribution in a lower population state would increase, but in a higher population state it decreases. It is shown that the multiplicative noise and the time delay play opposite roles in the tumor cell growth.展开更多
Photon-measurement density function （PMDF）, which is the kernel of fluorescence molecular tomography （FMT）, largely determines the accuracy of reconstruction result of FMT. Based on the direct method, we propose a...Photon-measurement density function （PMDF）, which is the kernel of fluorescence molecular tomography （FMT）, largely determines the accuracy of reconstruction result of FMT. Based on the direct method, we propose an expression of PMDF in FMT, which is derived from the finite element method （FEM） solution of the diffusion equation. Compared with the traditional expression based on the perturbation method, the accuracy of expression based on the direct method is shown in theory. Lastly the reconstruction results of phantoms prove this accuracy in experiment.展开更多
The advent of the big data era creates both opportunities and challenges for traditional Chinese medicine （TCM）. This study describes the origin, concept, connotation, and value of studies regarding the scientific c...The advent of the big data era creates both opportunities and challenges for traditional Chinese medicine （TCM）. This study describes the origin, concept, connotation, and value of studies regarding the scientific computation of TCM. It also discusses the integration of science, technology, and medicine under the guidance of the paradigm of real-world, clinical scientific research. TCM clinical diagnosis, treatment, and knowledge were traditionally limited to literature and sensation levels; however, primary methods are used to convert them into statistics, such as the methods of feature subset optimizing, multi-label learning, and complex networks based on complexity, intelligence, data, and computing sciences. Furthermore, these methods are applied in the modeling and analysis of the various complex relationships in individualized clinical diagnosis and treatment, as well as in decision-making related to such diagnosis and treatment. Thus, these methods strongly support the real-world clinical research paradigm of TCM.展开更多
基金Taishan Young Scholars Program of Shandong Province,Key Development Program for Basic Research of Shandong Province(ZR2020ZD44).
文摘Universal lesion detection(ULD)methods for computed tomography(CT)images play a vital role in the modern clinical medicine and intelligent automation.It is well known that single 2D CT slices lack spatial-temporal characteristics and contextual information compared to 3D CT blocks.However,3D CT blocks necessitate significantly higher hardware resources during the learning phase.Therefore,efficiently exploiting temporal correlation and spatial-temporal features of 2D CT slices is crucial for ULD tasks.In this paper,we propose a ULD network with the enhanced temporal correlation for this purpose,named TCE-Net.The designed TCE module is applied to enrich the discriminate feature representation of multiple sequential CT slices.Besides,we employ multi-scale feature maps to facilitate the localization and detection of lesions in various sizes.Extensive experiments are conducted on the DeepLesion benchmark demonstrate that thismethod achieves 66.84%and 78.18%for FS@0.5 and FS@1.0,respectively,outperforming compared state-of-the-art methods.
基金Supported by the National Natural Science Foundation of China under Grant No 10872014.
文摘We examine how noise interacts with encoding mechanisms of neuronal stimulus in a cold receptor. From ISI series and bifurcation diagrams it is shown that there are considerable differences in interval distributions and impulse patterns caused by purely deterministic simulations and noisy simulations. The ISI-distance can be used as an effective and powerful way to measure the noise effects on spike trains of the cold receptor quantitatively. It is also found that spike trains observed in cold receptors can be more strongly affected by noise for low temperatures than for high temperatures in some aspects; meanwhile, the spike train has greater variability with increasing noise intensity.
基金Supported by the National Natural Science Foundation of China under Grant No 10975063, and the Fundamental Research Pund for Physics and Mathematics of Lanzhou University.
文摘We study the dynamics of tumor cell growth with time-delayed feedback driven by multiplicative noise in an asymmetrical bistable potential well. For a small delay time, the analytical solutions of the probability distribution and the first passage time show that, with the increasing delay time, the peak of the probability distribution in a lower population state would increase, but in a higher population state it decreases. It is shown that the multiplicative noise and the time delay play opposite roles in the tumor cell growth.
基金Supported by the National High-Tech Research and Development Program of China （2006AA020801）, the National Natural Science Foundation of China （61078072）, and the Specialized Research Fund for the Doctoral Program of Higher Education of China （20070487058）.
文摘Photon-measurement density function （PMDF）, which is the kernel of fluorescence molecular tomography （FMT）, largely determines the accuracy of reconstruction result of FMT. Based on the direct method, we propose an expression of PMDF in FMT, which is derived from the finite element method （FEM） solution of the diffusion equation. Compared with the traditional expression based on the perturbation method, the accuracy of expression based on the direct method is shown in theory. Lastly the reconstruction results of phantoms prove this accuracy in experiment.
文摘The advent of the big data era creates both opportunities and challenges for traditional Chinese medicine （TCM）. This study describes the origin, concept, connotation, and value of studies regarding the scientific computation of TCM. It also discusses the integration of science, technology, and medicine under the guidance of the paradigm of real-world, clinical scientific research. TCM clinical diagnosis, treatment, and knowledge were traditionally limited to literature and sensation levels; however, primary methods are used to convert them into statistics, such as the methods of feature subset optimizing, multi-label learning, and complex networks based on complexity, intelligence, data, and computing sciences. Furthermore, these methods are applied in the modeling and analysis of the various complex relationships in individualized clinical diagnosis and treatment, as well as in decision-making related to such diagnosis and treatment. Thus, these methods strongly support the real-world clinical research paradigm of TCM.
