Introduction: To investigate the inter-observer and inter-modality variabilities of two imaging guided equipments—cone-beam computed tomography (CBCT) and ultrasound (US) in kidney stereotactic body radiotherapy. Met...Introduction: To investigate the inter-observer and inter-modality variabilities of two imaging guided equipments—cone-beam computed tomography (CBCT) and ultrasound (US) in kidney stereotactic body radiotherapy. Methods: A renal metastasis case implanted with three gold anchor fiducial markers was firstly scanned by US to acquire a 3-dimension US image and followed by 4-dimension CBCT in every fraction. Seven observers retrospectively registered the pre-treatment images with the corresponding reference images based on the gold markers. Registration uncertainty of the observers between two imaging modalities was evaluated. Results: The uncertainties over whole treatment course in CBCT were 0.88 mm, 1.94 mm and 0.86 mm in lateral, longitudinal and vertical directions respectively;while 0.8 mm, 0.97 mm and 1.36 mm were found in US. Conclusion: The greatest uncertainty was found in longitudinal direction in CBCT due to the fact that the respiration motion is the most rigorous in cranial-caudal direction. In US, since the probe was hold almost in upright position, the strong echo in vertical direction was attributed to the greatest uncertainty for such direction.展开更多
It is common that airlines encounter a disruption of a flight schedule,which is mainly caused by resource shortages.In case of a disruption,subject to scarce resources,most of airlines lose flexibility of performing a...It is common that airlines encounter a disruption of a flight schedule,which is mainly caused by resource shortages.In case of a disruption,subject to scarce resources,most of airlines lose flexibility of performing aircraft recovery on the basis of business interest priorities and need to delay,swap,and cancel flights.This paper proposes an air-rail inter-modal strategy to incorporate a High-Speed Rail(HSR)transport mode into an aviation network for aircraft recovery.The air-rail inter-modal strategy focuses on occasionally operational integration of existing airside and HSR infrastructure capacities.It is different from air-rail cooperation implemented in Europe which emphasizes a long-term strategy.In addition to modelling the air-rail inter-modal strategy,an inter-modal time-band network is presented.Modelling is applied to a pure aviation network and the inter-modal network.Comparison results show that the inter-modal air-rail strategy helps to reduce the number of cancelled flights and the total disruption cost.展开更多
A novel online Differential Mode Group Delay(DMGD)monitoring method based on four-wave mixing(FWM) in few mode fiber(FMF) transmission system is proposed, and the DMGD monitoring is achieved on the whole range of 15-5...A novel online Differential Mode Group Delay(DMGD)monitoring method based on four-wave mixing(FWM) in few mode fiber(FMF) transmission system is proposed, and the DMGD monitoring is achieved on the whole range of 15-50 ps/km. Detection principle is deduced and relationship of the power of idler waves and DMGD is analyzed. With various chromatic dispersion(CD)values, different line widths and different optical signal noise ratio(OSNR) values, the simulations are carried out. The simulation results show that this new DMGD monitoring method is less affected by different line widths and has a high tolerance for OSNR.展开更多
Significant breakthroughs in medical image registration have been achieved using deep neural networks(DNNs).However,DNN-based end-to-end registration methods often require large quantities of data or adequate annotati...Significant breakthroughs in medical image registration have been achieved using deep neural networks(DNNs).However,DNN-based end-to-end registration methods often require large quantities of data or adequate annotations for training.To leverage the intensity information of abundant unlabeled images,unsupervised registration methods commonly employ intensity-based similarity measures to optimize the network parameters.However,finding a sufficiently robust measure can be challenging for specific registration applications.Weakly supervised registration methods use anatomical labels to estimate the deformation between images.High-level structural information in label images is more reliable and practical for estimating the voxel correspondence of anatomic regions of interest between images,whereas label images are extremely difficult to collect.In this paper,we propose a two-stage semi-supervised learning framework for medical image registration,which consists of unsupervised and weakly supervised registration networks.The proposed semi-supervised learning framework is trained with intensity information from available images,label information from a relatively small number of labeled images and pseudo-label information from unlabeled images.Experimental results on two datasets(cardiac and abdominal images)demonstrate the efficacy and efficiency of this method in intra-and inter-modality medical image registrations,as well as its superior performance when a vast amount of unlabeled data and a small set of annotations are available.Our code is publicly available at at https://github.com/jdq818/SeRN.展开更多
Mode-and polarization-division multiplexing offer new dimensions to increase the transmission capacity of optical communications. Selective switches are key components in reconfigurable optical network nodes. An on-ch...Mode-and polarization-division multiplexing offer new dimensions to increase the transmission capacity of optical communications. Selective switches are key components in reconfigurable optical network nodes. An on-chip silicon 2 × 2 mode-and polarization-selective switch that can route four data channels on two modes and two polarizations simultaneously is proposed and experimentally demonstrated for the first time, to the best of our knowledge. The overall insertion losses are lower than 8.6 d B. To reduce the inter-modal crosstalk, polarization beam splitters are added to filter the undesired polarizations or modes. The measured inter-modal andintra-modal crosstalk values are below-23.2 and-22.8 d B for all the channels, respectively.展开更多
文摘Introduction: To investigate the inter-observer and inter-modality variabilities of two imaging guided equipments—cone-beam computed tomography (CBCT) and ultrasound (US) in kidney stereotactic body radiotherapy. Methods: A renal metastasis case implanted with three gold anchor fiducial markers was firstly scanned by US to acquire a 3-dimension US image and followed by 4-dimension CBCT in every fraction. Seven observers retrospectively registered the pre-treatment images with the corresponding reference images based on the gold markers. Registration uncertainty of the observers between two imaging modalities was evaluated. Results: The uncertainties over whole treatment course in CBCT were 0.88 mm, 1.94 mm and 0.86 mm in lateral, longitudinal and vertical directions respectively;while 0.8 mm, 0.97 mm and 1.36 mm were found in US. Conclusion: The greatest uncertainty was found in longitudinal direction in CBCT due to the fact that the respiration motion is the most rigorous in cranial-caudal direction. In US, since the probe was hold almost in upright position, the strong echo in vertical direction was attributed to the greatest uncertainty for such direction.
基金co-supported by the Tianjin Natural Science Foundation, China (No. 18JCQNJC04300)the National Natural Science Foundation of China (No. 71801215)the Foundation for University Key Teacher by the Ministry of Education of China (Nos. 3122018C033, 3122015L010)
文摘It is common that airlines encounter a disruption of a flight schedule,which is mainly caused by resource shortages.In case of a disruption,subject to scarce resources,most of airlines lose flexibility of performing aircraft recovery on the basis of business interest priorities and need to delay,swap,and cancel flights.This paper proposes an air-rail inter-modal strategy to incorporate a High-Speed Rail(HSR)transport mode into an aviation network for aircraft recovery.The air-rail inter-modal strategy focuses on occasionally operational integration of existing airside and HSR infrastructure capacities.It is different from air-rail cooperation implemented in Europe which emphasizes a long-term strategy.In addition to modelling the air-rail inter-modal strategy,an inter-modal time-band network is presented.Modelling is applied to a pure aviation network and the inter-modal network.Comparison results show that the inter-modal air-rail strategy helps to reduce the number of cancelled flights and the total disruption cost.
基金supported by the National Science Foundation of China (61574080)Research Center of Optical Communications Engineering & Technology,Jiangsu Province (ZXF201803)
文摘A novel online Differential Mode Group Delay(DMGD)monitoring method based on four-wave mixing(FWM) in few mode fiber(FMF) transmission system is proposed, and the DMGD monitoring is achieved on the whole range of 15-50 ps/km. Detection principle is deduced and relationship of the power of idler waves and DMGD is analyzed. With various chromatic dispersion(CD)values, different line widths and different optical signal noise ratio(OSNR) values, the simulations are carried out. The simulation results show that this new DMGD monitoring method is less affected by different line widths and has a high tolerance for OSNR.
文摘Significant breakthroughs in medical image registration have been achieved using deep neural networks(DNNs).However,DNN-based end-to-end registration methods often require large quantities of data or adequate annotations for training.To leverage the intensity information of abundant unlabeled images,unsupervised registration methods commonly employ intensity-based similarity measures to optimize the network parameters.However,finding a sufficiently robust measure can be challenging for specific registration applications.Weakly supervised registration methods use anatomical labels to estimate the deformation between images.High-level structural information in label images is more reliable and practical for estimating the voxel correspondence of anatomic regions of interest between images,whereas label images are extremely difficult to collect.In this paper,we propose a two-stage semi-supervised learning framework for medical image registration,which consists of unsupervised and weakly supervised registration networks.The proposed semi-supervised learning framework is trained with intensity information from available images,label information from a relatively small number of labeled images and pseudo-label information from unlabeled images.Experimental results on two datasets(cardiac and abdominal images)demonstrate the efficacy and efficiency of this method in intra-and inter-modality medical image registrations,as well as its superior performance when a vast amount of unlabeled data and a small set of annotations are available.Our code is publicly available at at https://github.com/jdq818/SeRN.
基金National Natural Science Foundation of China(NSFC)(61235007,61505104,61605112)863 High-Tech Program(2015AA017001)Science and Technology Commission of Shanghai Municipality(STCSM)(15ZR1422800,16XD1401400)
文摘Mode-and polarization-division multiplexing offer new dimensions to increase the transmission capacity of optical communications. Selective switches are key components in reconfigurable optical network nodes. An on-chip silicon 2 × 2 mode-and polarization-selective switch that can route four data channels on two modes and two polarizations simultaneously is proposed and experimentally demonstrated for the first time, to the best of our knowledge. The overall insertion losses are lower than 8.6 d B. To reduce the inter-modal crosstalk, polarization beam splitters are added to filter the undesired polarizations or modes. The measured inter-modal andintra-modal crosstalk values are below-23.2 and-22.8 d B for all the channels, respectively.
