Sinus floor elevation with a lateral window approach requires bone graft(BG)to ensure sufficient bone mass,and it is necessary to measure and analyse the BG region for follow-up of postoperative patients.However,the B...Sinus floor elevation with a lateral window approach requires bone graft(BG)to ensure sufficient bone mass,and it is necessary to measure and analyse the BG region for follow-up of postoperative patients.However,the BG region from cone-beam computed tomography(CBCT)images is connected to the margin of the maxillary sinus,and its boundary is blurred.Common segmentation methods are usually performed manually by experienced doctors,and are complicated by challenges such as low efficiency and low precision.In this study,an auto-segmentation approach was applied to the BG region within the maxillary sinus based on an atrous spatial pyramid convolution(ASPC)network.The ASPC module was adopted using residual connections to compose multiple atrous convolutions,which could extract more features on multiple scales.Subsequently,a segmentation network of the BG region with multiple ASPC modules was established,which effectively improved the segmentation performance.Although the training data were insufficient,our networks still achieved good auto-segmentation results,with a dice coefficient(Dice)of 87.13%,an Intersection over Union(Iou)of 78.01%,and a sensitivity of 95.02%.Compared with other methods,our method achieved a better segmentation effect,and effectively reduced the misjudgement of segmentation.Our method can thus be used to implement automatic segmentation of the BG region and improve doctors’work efficiency,which is of great importance for developing preliminary studies on the measurement of postoperative BG within the maxillary sinus.展开更多
This study presents an advanced method for post-mortem person identification using the segmentation of skeletal structures from chest X-ray images.The proposed approach employs the Attention U-Net architecture,enhance...This study presents an advanced method for post-mortem person identification using the segmentation of skeletal structures from chest X-ray images.The proposed approach employs the Attention U-Net architecture,enhanced with gated attention mechanisms,to refine segmentation by emphasizing spatially relevant anatomical features while suppressing irrelevant details.By isolating skeletal structures which remain stable over time compared to soft tissues,this method leverages bones as reliable biometric markers for identity verification.The model integrates custom-designed encoder and decoder blocks with attention gates,achieving high segmentation precision.To evaluate the impact of architectural choices,we conducted an ablation study comparing Attention U-Net with and without attentionmechanisms,alongside an analysis of data augmentation effects.Training and evaluation were performed on a curated chest X-ray dataset,with segmentation performance measured using Dice score,precision,and loss functions,achieving over 98% precision and 94% Dice score.The extracted bone structures were further processed to derive unique biometric patterns,enabling robust and privacy-preserving person identification.Our findings highlight the effectiveness of attentionmechanisms in improving segmentation accuracy and underscore the potential of chest bonebased biometrics in forensic and medical imaging.This work paves the way for integrating artificial intelligence into real-world forensic workflows,offering a non-invasive and reliable solution for post-mortem identification.展开更多
Objective:The aims of this study were to investigate the clinical applicability of 3D segmentation in measuring cochlear anatomical parameters,explore factors that influence the insertion angle of cochlear implant ele...Objective:The aims of this study were to investigate the clinical applicability of 3D segmentation in measuring cochlear anatomical parameters,explore factors that influence the insertion angle of cochlear implant electrodes in patients with inner ear malformations,and determine the value of 3D segmentation in predicting cochlear implant electrode insertion depth by simulating electrode implantation in a reconstructed 3D model.Methods:Data from 208 temporal bone CT scans of patients with a variety of inner ear malformations(including the CH,IP-Ⅰ,IP-Ⅱ,and IP-Ⅲtypes)who underwent cochlear implantation at our center were retrospectively analyzed.Preoperative temporal bone CT data were subjected to three-dimensional(3D)segmentation of the cochlea with a 3D slicer.Results:Cochlear malformation types,including IP typesⅠ(42 ears),Ⅱ(278ears),Ⅲ(20 ears),and CH(65 ears),were diagnosed and measured in 208 preoperative CT datasets.Cochlear anatomical parameters and electrode length were correlated,which partially explained the variations in electrode insertion angle.The mean angle of implantation among the enrolled patients was 564.33°,and the mean implantation angle prediction error in the 3D segmentation was|23.74|°.Conclusion:Three-dimensional segmentation from temporal bone CT is valuable for surgeons,especially in treating patients with inner ear malformation.Such insights will help surgeons understand overall anatomical variations,predict electrode implantation depth,and complete preoperative imaging assessments for cochlear implant insertion depth in patients with inner ear malformations.展开更多
Morphological analyses are key outcome assessments for nerve regeneration studies but are historically limited to tissue sections.Novel optical tissue clearing techniques enabling three-dimensional imaging of entire o...Morphological analyses are key outcome assessments for nerve regeneration studies but are historically limited to tissue sections.Novel optical tissue clearing techniques enabling three-dimensional imaging of entire organs at a subcellular resolution have revolutionized morphological studies of the brain.To extend their applicability to experimental nerve repair studies we adapted these techniques to nerves and their motor and sensory targets in rats.The solvent-based protocols rendered harvested peripheral nerves and their target organs transparent within 24 hours while preserving tissue architecture and fluorescence.The optical clearing was compatible with conventional laboratory techniques,including retrograde labeling studies,and computational image segmentation,providing fast and precise cell quantitation.Further,optically cleared organs enabled three-dimensional morphometry at an unprecedented scale including dermatome-wide innervation studies,tracing of intramuscular nerve branches or mapping of neurovascular networks.Given their wide-ranging applicability,rapid processing times,and low costs,tissue clearing techniques are likely to be a key technology for next-generation nerve repair studies.All procedures were approved by the Hospital for Sick Children’s Laboratory Animal Services Committee(49871/9)on November 9,2019.展开更多
Background Given that three-dimensional finite element models have been successfully used to analyze biomechanics in orthopedics-related research, this study aimed to establish a finite element model of the pelvic bon...Background Given that three-dimensional finite element models have been successfully used to analyze biomechanics in orthopedics-related research, this study aimed to establish a finite element model of the pelvic bone and three-fin acetabular component and evaluate biomechanical changes in this model after implantation of a three-fin acetabular prosthesis in a superior segmental bone defect of the acetabulum.展开更多
基金the National Key Research and Development Program of China(No.2017YFB1302900)the National Natural Science Foundation of China(Nos.81971709,M-0019,and 82011530141)+2 种基金the Foundation of Science and Technology Commission of Shanghai Municipality(Nos.19510712200,and 20490740700)the Shanghai Jiao Tong University Foundation on Medical and Technological Joint Science Research(Nos.ZH2018ZDA15,YG2019ZDA06,and ZH2018QNA23)the 2020 Key Research Project of Xiamen Municipal Government(No.3502Z20201030)。
文摘Sinus floor elevation with a lateral window approach requires bone graft(BG)to ensure sufficient bone mass,and it is necessary to measure and analyse the BG region for follow-up of postoperative patients.However,the BG region from cone-beam computed tomography(CBCT)images is connected to the margin of the maxillary sinus,and its boundary is blurred.Common segmentation methods are usually performed manually by experienced doctors,and are complicated by challenges such as low efficiency and low precision.In this study,an auto-segmentation approach was applied to the BG region within the maxillary sinus based on an atrous spatial pyramid convolution(ASPC)network.The ASPC module was adopted using residual connections to compose multiple atrous convolutions,which could extract more features on multiple scales.Subsequently,a segmentation network of the BG region with multiple ASPC modules was established,which effectively improved the segmentation performance.Although the training data were insufficient,our networks still achieved good auto-segmentation results,with a dice coefficient(Dice)of 87.13%,an Intersection over Union(Iou)of 78.01%,and a sensitivity of 95.02%.Compared with other methods,our method achieved a better segmentation effect,and effectively reduced the misjudgement of segmentation.Our method can thus be used to implement automatic segmentation of the BG region and improve doctors’work efficiency,which is of great importance for developing preliminary studies on the measurement of postoperative BG within the maxillary sinus.
基金funded by Umm Al-Qura University,Saudi Arabia under grant number:25UQU4300346GSSR08.
文摘This study presents an advanced method for post-mortem person identification using the segmentation of skeletal structures from chest X-ray images.The proposed approach employs the Attention U-Net architecture,enhanced with gated attention mechanisms,to refine segmentation by emphasizing spatially relevant anatomical features while suppressing irrelevant details.By isolating skeletal structures which remain stable over time compared to soft tissues,this method leverages bones as reliable biometric markers for identity verification.The model integrates custom-designed encoder and decoder blocks with attention gates,achieving high segmentation precision.To evaluate the impact of architectural choices,we conducted an ablation study comparing Attention U-Net with and without attentionmechanisms,alongside an analysis of data augmentation effects.Training and evaluation were performed on a curated chest X-ray dataset,with segmentation performance measured using Dice score,precision,and loss functions,achieving over 98% precision and 94% Dice score.The extracted bone structures were further processed to derive unique biometric patterns,enabling robust and privacy-preserving person identification.Our findings highlight the effectiveness of attentionmechanisms in improving segmentation accuracy and underscore the potential of chest bonebased biometrics in forensic and medical imaging.This work paves the way for integrating artificial intelligence into real-world forensic workflows,offering a non-invasive and reliable solution for post-mortem identification.
基金supported by the National Key Research and Development Program of China(grant no.2022YFC2402705)National Municipal Natural Science Foundation(grant no.82471161)Beijing Municipal Natural Science Foundation(grant no.7244308)。
文摘Objective:The aims of this study were to investigate the clinical applicability of 3D segmentation in measuring cochlear anatomical parameters,explore factors that influence the insertion angle of cochlear implant electrodes in patients with inner ear malformations,and determine the value of 3D segmentation in predicting cochlear implant electrode insertion depth by simulating electrode implantation in a reconstructed 3D model.Methods:Data from 208 temporal bone CT scans of patients with a variety of inner ear malformations(including the CH,IP-Ⅰ,IP-Ⅱ,and IP-Ⅲtypes)who underwent cochlear implantation at our center were retrospectively analyzed.Preoperative temporal bone CT data were subjected to three-dimensional(3D)segmentation of the cochlea with a 3D slicer.Results:Cochlear malformation types,including IP typesⅠ(42 ears),Ⅱ(278ears),Ⅲ(20 ears),and CH(65 ears),were diagnosed and measured in 208 preoperative CT datasets.Cochlear anatomical parameters and electrode length were correlated,which partially explained the variations in electrode insertion angle.The mean angle of implantation among the enrolled patients was 564.33°,and the mean implantation angle prediction error in the 3D segmentation was|23.74|°.Conclusion:Three-dimensional segmentation from temporal bone CT is valuable for surgeons,especially in treating patients with inner ear malformation.Such insights will help surgeons understand overall anatomical variations,predict electrode implantation depth,and complete preoperative imaging assessments for cochlear implant insertion depth in patients with inner ear malformations.
基金the German Research Foundation(DA 2255/1-1,to SCD).
文摘Morphological analyses are key outcome assessments for nerve regeneration studies but are historically limited to tissue sections.Novel optical tissue clearing techniques enabling three-dimensional imaging of entire organs at a subcellular resolution have revolutionized morphological studies of the brain.To extend their applicability to experimental nerve repair studies we adapted these techniques to nerves and their motor and sensory targets in rats.The solvent-based protocols rendered harvested peripheral nerves and their target organs transparent within 24 hours while preserving tissue architecture and fluorescence.The optical clearing was compatible with conventional laboratory techniques,including retrograde labeling studies,and computational image segmentation,providing fast and precise cell quantitation.Further,optically cleared organs enabled three-dimensional morphometry at an unprecedented scale including dermatome-wide innervation studies,tracing of intramuscular nerve branches or mapping of neurovascular networks.Given their wide-ranging applicability,rapid processing times,and low costs,tissue clearing techniques are likely to be a key technology for next-generation nerve repair studies.All procedures were approved by the Hospital for Sick Children’s Laboratory Animal Services Committee(49871/9)on November 9,2019.
文摘Background Given that three-dimensional finite element models have been successfully used to analyze biomechanics in orthopedics-related research, this study aimed to establish a finite element model of the pelvic bone and three-fin acetabular component and evaluate biomechanical changes in this model after implantation of a three-fin acetabular prosthesis in a superior segmental bone defect of the acetabulum.
