Basic features Bangonghu—Dingqing Suture is the medial and western segment of the Bangonghu—Nujiang Suture which many researchers called as ,and it is often regarded as the Qiangtang Massif boundary line in the nort...Basic features Bangonghu—Dingqing Suture is the medial and western segment of the Bangonghu—Nujiang Suture which many researchers called as ,and it is often regarded as the Qiangtang Massif boundary line in the northern side and the Lasa (Gangdisi) Massif in the souther. The era of the ophiolites spreading along the Bangonghu\|Dingqing suture include every period of the whole Jurassic, and the spreading of the ophiolites has distinct segmentation. From west to east there are Ritu segment,Gaize segment,Dongqiao segment and Dingqing segment.Between the Gaize segment and Dongqiao one ,that is ,between the E89°and E86°40′,no ophiolites are discovered in the surface.Aeromagnetic data shows that the magnetic field of this segment is quite gentle,there are no difference from its adjacent northern and southern sides. When its east adjacent segment extends into this segment, the high areomagnetic anomaly belt corresponding to of the Dongqiao ophiolite disappear abruptly. Apparently,it is impossible for the ophiolites to develop in such a deep crust of the same segment.展开更多
Regular detection and repair for lining cracks are necessary to guarantee the safety and stability of tunnels.The development of computer vision has greatly promoted structural health monitoring.This study proposes a ...Regular detection and repair for lining cracks are necessary to guarantee the safety and stability of tunnels.The development of computer vision has greatly promoted structural health monitoring.This study proposes a novel encoder–decoder structure,CrackRecNet,for semantic segmentation of lining segment cracks by integrating improved VGG-19 into the U-Net architecture.An image acquisition equipment is designed based on a camera,3-dimensional printing(3DP)bracket and two laser rangefinders.A tunnel concrete structure crack(TCSC)image data set,containing images collected from a double-shield tunnel boring machines(TBM)tunnel in China,was established.Through data preprocessing operations,such as brightness adjustment,pixel resolution adjustment,flipping,splitting and annotation,2880 image samples with pixel resolution of 448×448 were prepared.The model was implemented by Pytorch in PyCharm processed with 4 NVIDIA TITAN V GPUs.In the experiments,the proposed CrackRecNet showed better prediction performance than U-Net,TernausNet,and ResU-Net.This paper also discusses GPU parallel acceleration effect and the crack maximum width quantification.展开更多
Recently,Meta AI Research approaches a general,promptable segment anything model(SAM)pre-trained on an unprecedentedly large segmentation dataset(SA-1B).Without a doubt,the emergence of SAM will yield significant bene...Recently,Meta AI Research approaches a general,promptable segment anything model(SAM)pre-trained on an unprecedentedly large segmentation dataset(SA-1B).Without a doubt,the emergence of SAM will yield significant benefits for a wide array of practical image segmentation applications.In this study,we conduct a series of intriguing investigations into the performance of SAM across various applications,particularly in the fields of natural images,agriculture,manufacturing,remote sensing and healthcare.We analyze and discuss the benefits and limitations of SAM,while also presenting an outlook on its future development in segmentation tasks.By doing so,we aim to give a comprehensive understanding of SAM's practical applications.This work is expected to provide insights that facilitate future research activities toward generic segmentation.Source code is publicly available at https://github.com/LiuTingWed/SAM-Not-Perfect.展开更多
Background:Optical coherence tomography(OCT)is a non-invasive imaging system that can be used to obtain images of the anterior segment.Automatic segmentation of these images will enable them to be used to construct pa...Background:Optical coherence tomography(OCT)is a non-invasive imaging system that can be used to obtain images of the anterior segment.Automatic segmentation of these images will enable them to be used to construct patient specific biomechanical models of the human eye.These models could be used to help with treatment planning and diagnosis of patients.Methods:A novel graph cut technique using regional and shape terms was developed.It was evaluated by segmenting 39 OCT images of the anterior segment.The results of this were compared with manual segmentation and a previously reported level set segmentation technique.Three different comparison techniques were used:Dice’s similarity coefficient(DSC),mean unsigned surface positioning error(MSPE),and 95%Hausdorff distance(HD).A paired t-test was used to compare the results of different segmentation techniques.Results:When comparison with manual segmentation was performed,a mean DSC value of 0.943±0.020 was achieved,outperforming other previously published techniques.A substantial reduction in processing time was also achieved using this method.Conclusions:We have developed a new segmentation technique that is both fast and accurate.This has the potential to be used to aid diagnostics and treatment planning.展开更多
文摘Basic features Bangonghu—Dingqing Suture is the medial and western segment of the Bangonghu—Nujiang Suture which many researchers called as ,and it is often regarded as the Qiangtang Massif boundary line in the northern side and the Lasa (Gangdisi) Massif in the souther. The era of the ophiolites spreading along the Bangonghu\|Dingqing suture include every period of the whole Jurassic, and the spreading of the ophiolites has distinct segmentation. From west to east there are Ritu segment,Gaize segment,Dongqiao segment and Dingqing segment.Between the Gaize segment and Dongqiao one ,that is ,between the E89°and E86°40′,no ophiolites are discovered in the surface.Aeromagnetic data shows that the magnetic field of this segment is quite gentle,there are no difference from its adjacent northern and southern sides. When its east adjacent segment extends into this segment, the high areomagnetic anomaly belt corresponding to of the Dongqiao ophiolite disappear abruptly. Apparently,it is impossible for the ophiolites to develop in such a deep crust of the same segment.
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.52179105 and 41941019)Science and Technology Innovation Project of Quanmutang Engineering.
文摘Regular detection and repair for lining cracks are necessary to guarantee the safety and stability of tunnels.The development of computer vision has greatly promoted structural health monitoring.This study proposes a novel encoder–decoder structure,CrackRecNet,for semantic segmentation of lining segment cracks by integrating improved VGG-19 into the U-Net architecture.An image acquisition equipment is designed based on a camera,3-dimensional printing(3DP)bracket and two laser rangefinders.A tunnel concrete structure crack(TCSC)image data set,containing images collected from a double-shield tunnel boring machines(TBM)tunnel in China,was established.Through data preprocessing operations,such as brightness adjustment,pixel resolution adjustment,flipping,splitting and annotation,2880 image samples with pixel resolution of 448×448 were prepared.The model was implemented by Pytorch in PyCharm processed with 4 NVIDIA TITAN V GPUs.In the experiments,the proposed CrackRecNet showed better prediction performance than U-Net,TernausNet,and ResU-Net.This paper also discusses GPU parallel acceleration effect and the crack maximum width quantification.
基金supported by the Mitacs,CFI-JELF and NSERC Discovery grants.
文摘Recently,Meta AI Research approaches a general,promptable segment anything model(SAM)pre-trained on an unprecedentedly large segmentation dataset(SA-1B).Without a doubt,the emergence of SAM will yield significant benefits for a wide array of practical image segmentation applications.In this study,we conduct a series of intriguing investigations into the performance of SAM across various applications,particularly in the fields of natural images,agriculture,manufacturing,remote sensing and healthcare.We analyze and discuss the benefits and limitations of SAM,while also presenting an outlook on its future development in segmentation tasks.By doing so,we aim to give a comprehensive understanding of SAM's practical applications.This work is expected to provide insights that facilitate future research activities toward generic segmentation.Source code is publicly available at https://github.com/LiuTingWed/SAM-Not-Perfect.
文摘Background:Optical coherence tomography(OCT)is a non-invasive imaging system that can be used to obtain images of the anterior segment.Automatic segmentation of these images will enable them to be used to construct patient specific biomechanical models of the human eye.These models could be used to help with treatment planning and diagnosis of patients.Methods:A novel graph cut technique using regional and shape terms was developed.It was evaluated by segmenting 39 OCT images of the anterior segment.The results of this were compared with manual segmentation and a previously reported level set segmentation technique.Three different comparison techniques were used:Dice’s similarity coefficient(DSC),mean unsigned surface positioning error(MSPE),and 95%Hausdorff distance(HD).A paired t-test was used to compare the results of different segmentation techniques.Results:When comparison with manual segmentation was performed,a mean DSC value of 0.943±0.020 was achieved,outperforming other previously published techniques.A substantial reduction in processing time was also achieved using this method.Conclusions:We have developed a new segmentation technique that is both fast and accurate.This has the potential to be used to aid diagnostics and treatment planning.
