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Artificial Intelligence for Medical Image Analysis of NeuroImaging Data
| Artificial Intelligence for Medical Image Analysis of NeuroImaging Data |
| Autore | Zeng Nianyin |
| Pubbl/distr/stampa | Frontiers Media SA, 2020 |
| Descrizione fisica | 1 electronic resource (224 p.) |
| Soggetto topico |
Science: general issues
Neurosciences |
| Soggetto non controllato |
medical image analysis
artificial intelligence machine learning pattern recognition computational intelligence |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557216703321 |
Zeng Nianyin
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| Frontiers Media SA, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : 6th International Workshop and Challenge, CSI 2019, Shenzhen, China, October 17, 2019, Proceedings / / edited by Yunliang Cai, Liansheng Wang, Michel Audette, Guoyan Zheng, Shuo Li
| Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : 6th International Workshop and Challenge, CSI 2019, Shenzhen, China, October 17, 2019, Proceedings / / edited by Yunliang Cai, Liansheng Wang, Michel Audette, Guoyan Zheng, Shuo Li |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XII, 120 p. 63 illus., 50 illus. in color.) |
| Disciplina | 616.730754 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Machine learning Computers Education—Data processing Application software Image Processing and Computer Vision Machine Learning Information Systems and Communication Service Computers and Education Computer Appl. in Social and Behavioral Sciences |
| ISBN | 3-030-39752-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Regular Papers -- Detection of vertebral fractures in CT using 3D Convolutional Neural Networks -- Metastatic Vertebrae Segmentation for Use in a Clinical Pipeline -- Conditioned Variational Auto-Encoder for Detecting Osteoporotic Vertebral Fractures -- Vertebral Labelling in Radiographs: Learning a Coordinate Corrector to Enforce Spinal Shape -- Semi-supervised semantic segmentation of multiple lumbosacral structures on CT -- AASCE Challenge -- Accurate Automated Keypoint Detections for Spinal Curvature Estimation -- Seg4Reg Networks for Automated Spinal Curvature Estimation -- Automatic Spine Curvature Estimation by a Top-down Approach -- Automatic Cobb Angle Detection using Vertebra Detector and Vertebra Corners Regression -- Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaded Neural Networks -- Automated Spinal Curvature Assessment from X-Ray Images using Landmarks Estimation Network via Rotation Proposals -- A coarse-to-fine deep heatmap regression method for Adolescent Idiopathic Scoliosis Assessment -- Spinal Curve Guide Network(SCG-Net) for Accurate Automated Spinal Curvature Estimation -- A Multi-Task Learning Method for Direct Estimation of Spinal Curvature. |
| Record Nr. | UNISA-996418205603316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : 6th International Workshop and Challenge, CSI 2019, Shenzhen, China, October 17, 2019, Proceedings / / edited by Yunliang Cai, Liansheng Wang, Michel Audette, Guoyan Zheng, Shuo Li
| Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : 6th International Workshop and Challenge, CSI 2019, Shenzhen, China, October 17, 2019, Proceedings / / edited by Yunliang Cai, Liansheng Wang, Michel Audette, Guoyan Zheng, Shuo Li |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XII, 120 p. 63 illus., 50 illus. in color.) |
| Disciplina | 616.730754 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Machine learning Computers Education—Data processing Application software Image Processing and Computer Vision Machine Learning Information Systems and Communication Service Computers and Education Computer Appl. in Social and Behavioral Sciences |
| ISBN | 3-030-39752-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Regular Papers -- Detection of vertebral fractures in CT using 3D Convolutional Neural Networks -- Metastatic Vertebrae Segmentation for Use in a Clinical Pipeline -- Conditioned Variational Auto-Encoder for Detecting Osteoporotic Vertebral Fractures -- Vertebral Labelling in Radiographs: Learning a Coordinate Corrector to Enforce Spinal Shape -- Semi-supervised semantic segmentation of multiple lumbosacral structures on CT -- AASCE Challenge -- Accurate Automated Keypoint Detections for Spinal Curvature Estimation -- Seg4Reg Networks for Automated Spinal Curvature Estimation -- Automatic Spine Curvature Estimation by a Top-down Approach -- Automatic Cobb Angle Detection using Vertebra Detector and Vertebra Corners Regression -- Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaded Neural Networks -- Automated Spinal Curvature Assessment from X-Ray Images using Landmarks Estimation Network via Rotation Proposals -- A coarse-to-fine deep heatmap regression method for Adolescent Idiopathic Scoliosis Assessment -- Spinal Curve Guide Network(SCG-Net) for Accurate Automated Spinal Curvature Estimation -- A Multi-Task Learning Method for Direct Estimation of Spinal Curvature. |
| Record Nr. | UNINA-9910373927703321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : 5th International Workshop and Challenge, CSI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers / / edited by Guoyan Zheng, Daniel Belavy, Yunliang Cai, Shuo Li
| Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : 5th International Workshop and Challenge, CSI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers / / edited by Guoyan Zheng, Daniel Belavy, Yunliang Cai, Shuo Li |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (X, 181 p. 103 illus., 77 illus. in color.) |
| Disciplina | 616.730754 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Health informatics Computer communication systems Artificial intelligence Computer hardware Image Processing and Computer Vision Health Informatics Computer Communication Networks Artificial Intelligence Computer Hardware |
| ISBN | 3-030-13736-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Spinal Cord Gray Matter-White Matter Segmentation on Magnetic Resonance AMIRA Images with MD-GRU -- Predicting Scoliosis in DXA Scans Using Intermediate Representations -- Fast Registration of CT with Intra-operative Ultrasound Images for Spine Surgery -- Automated Grading of Modic Changes Using CNNs – Improving the Performance with Mix-up -- Error Estimation for Appearance Model Segmentation of Musculoskeletal Structures Using Multiple, Independent Sub-models -- Automated Segmentation of Intervertebral Disc using Fully Dilated Separable Deep Neural Networks -- Intensity Standardization of Skeleton in Follow-up Whole-Body MRI -- Towards a Deformable Multi-Surface Approach to Ligamentous Spine Models for Predictive Simulation-Based Scoliosis Surgery Planning -- Intervertebral Disc Segmentation Using Mathematical Morphology—A CNN-Free Approach. |
| Record Nr. | UNINA-9910337578003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : 5th International Workshop and Challenge, CSI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers / / edited by Guoyan Zheng, Daniel Belavy, Yunliang Cai, Shuo Li
| Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : 5th International Workshop and Challenge, CSI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers / / edited by Guoyan Zheng, Daniel Belavy, Yunliang Cai, Shuo Li |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (X, 181 p. 103 illus., 77 illus. in color.) |
| Disciplina | 616.730754 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Health informatics Computer communication systems Artificial intelligence Computer hardware Image Processing and Computer Vision Health Informatics Computer Communication Networks Artificial Intelligence Computer Hardware |
| ISBN | 3-030-13736-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Spinal Cord Gray Matter-White Matter Segmentation on Magnetic Resonance AMIRA Images with MD-GRU -- Predicting Scoliosis in DXA Scans Using Intermediate Representations -- Fast Registration of CT with Intra-operative Ultrasound Images for Spine Surgery -- Automated Grading of Modic Changes Using CNNs – Improving the Performance with Mix-up -- Error Estimation for Appearance Model Segmentation of Musculoskeletal Structures Using Multiple, Independent Sub-models -- Automated Segmentation of Intervertebral Disc using Fully Dilated Separable Deep Neural Networks -- Intensity Standardization of Skeleton in Follow-up Whole-Body MRI -- Towards a Deformable Multi-Surface Approach to Ligamentous Spine Models for Predictive Simulation-Based Scoliosis Surgery Planning -- Intervertebral Disc Segmentation Using Mathematical Morphology—A CNN-Free Approach. |
| Record Nr. | UNISA-996466445103316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : 4th International Workshop and Challenge, CSI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected Papers / / edited by Jianhua Yao, Tomaž Vrtovec, Guoyan Zheng, Alejandro Frangi, Ben Glocker, Shuo Li
| Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : 4th International Workshop and Challenge, CSI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected Papers / / edited by Jianhua Yao, Tomaž Vrtovec, Guoyan Zheng, Alejandro Frangi, Ben Glocker, Shuo Li |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (X, 147 p. 60 illus.) |
| Disciplina | 006.37 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Computer graphics Artificial intelligence Computer simulation Algorithms Image Processing and Computer Vision Pattern Recognition Computer Graphics Artificial Intelligence Simulation and Modeling Algorithm Analysis and Problem Complexity |
| ISBN | 3-319-55050-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | State-of-the-art techniques -- Novel and emerging analysis and visualization techniques -- Clinical challenges and open problems -- Major aspects of problems related to spine imaging -- Including clinical applications of spine imaging -- Computer aided diagnosis of spine conditions -- Computer aided detection of spine-related diseases -- Emerging computational imaging techniques for spinal diseases,.-Fast 3D reconstruction of spine, feature extraction, multiscale analysis, pattern recognition, image enhancement of spine imaging -- Image-guided spine intervention and treatment, multimodal image registration and fusion for spine imaging -- Novel visualization techniques, segmentation techniques for spine imaging, statistical and geometric modeling for spine and vertebra, spine and vertebra localization. |
| Record Nr. | UNINA-9910483822503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : Third International Workshop and Challenge, CSI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings / / edited by Tomaž Vrtovec, Jianhua Yao, Ben Glocker, Tobias Klinder, Alejandro Frangi, Guoyan Zheng, Shuo Li
| Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : Third International Workshop and Challenge, CSI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings / / edited by Tomaž Vrtovec, Jianhua Yao, Ben Glocker, Tobias Klinder, Alejandro Frangi, Guoyan Zheng, Shuo Li |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (X, 159 p. 61 illus.) |
| Disciplina | 616.730754 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Computer graphics Artificial intelligence Computer simulation Algorithms Image Processing and Computer Vision Pattern Recognition Computer Graphics Artificial Intelligence Simulation and Modeling Algorithm Analysis and Problem Complexity |
| ISBN | 3-319-41827-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Automated Pedicle Screw Size and Trajectory Planning by Maximization of Fastening Strength -- Automatic Modic Changes Classification in Spinal MRI -- Patient Registration via Topologically Encoded Depth Projection Images in Spine Surgery -- Automatic Localisation of Vertebrae in DXA Images Using Random Forest Regression Voting -- Robust CT to US 3D-3D Registration by Using Principal Component Analysis and Kalman Filtering -- Cortical Bone Thickness Estimation in CT Images: A Model-Based Approach Without Profile Fitting -- Multi-Atlas Segmentation with Joint Label Fusion of Osteoporotic Vertebral Compression Fractures on CT -- Statistical Shape Model Construction of Lumbar Vertebrae and Intervertebral Discs in Segmentation for Discectomy Surgery Simulation -- Automatic Intervertebral Discs Localization and Segmentation: A Vertebral Approach -- Segmentation of Intervertebral Discs in 3D MRI Data Using Multi-Atlas Based Registration -- Deformable Model-Based Segmentation of Intervertebral Discs from MR Spine Images by Using the SSC Descriptor -- 3D Intervertebral Disc Segmentation from MRI Using Supervoxel-Based CRFs -- Automatic Intervertebral Disc Localization and Segmentation in 3D MR Images Based on Regression Forests and Active Contours -- Localization and Segmentation of 3D Intervertebral Discs from MR Images via a Learning Based Method: A Validation Framework -- Automated Intervertebral Disc Segmentation Using Probabilistic Shape Estimation and Active Shape Models. . |
| Record Nr. | UNINA-9910484764303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : Third International Workshop and Challenge, CSI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings / / edited by Tomaž Vrtovec, Jianhua Yao, Ben Glocker, Tobias Klinder, Alejandro Frangi, Guoyan Zheng, Shuo Li
| Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : Third International Workshop and Challenge, CSI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings / / edited by Tomaž Vrtovec, Jianhua Yao, Ben Glocker, Tobias Klinder, Alejandro Frangi, Guoyan Zheng, Shuo Li |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (X, 159 p. 61 illus.) |
| Disciplina | 616.730754 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Computer graphics Artificial intelligence Computer simulation Algorithms Image Processing and Computer Vision Pattern Recognition Computer Graphics Artificial Intelligence Simulation and Modeling Algorithm Analysis and Problem Complexity |
| ISBN | 3-319-41827-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Automated Pedicle Screw Size and Trajectory Planning by Maximization of Fastening Strength -- Automatic Modic Changes Classification in Spinal MRI -- Patient Registration via Topologically Encoded Depth Projection Images in Spine Surgery -- Automatic Localisation of Vertebrae in DXA Images Using Random Forest Regression Voting -- Robust CT to US 3D-3D Registration by Using Principal Component Analysis and Kalman Filtering -- Cortical Bone Thickness Estimation in CT Images: A Model-Based Approach Without Profile Fitting -- Multi-Atlas Segmentation with Joint Label Fusion of Osteoporotic Vertebral Compression Fractures on CT -- Statistical Shape Model Construction of Lumbar Vertebrae and Intervertebral Discs in Segmentation for Discectomy Surgery Simulation -- Automatic Intervertebral Discs Localization and Segmentation: A Vertebral Approach -- Segmentation of Intervertebral Discs in 3D MRI Data Using Multi-Atlas Based Registration -- Deformable Model-Based Segmentation of Intervertebral Discs from MR Spine Images by Using the SSC Descriptor -- 3D Intervertebral Disc Segmentation from MRI Using Supervoxel-Based CRFs -- Automatic Intervertebral Disc Localization and Segmentation in 3D MR Images Based on Regression Forests and Active Contours -- Localization and Segmentation of 3D Intervertebral Discs from MR Images via a Learning Based Method: A Validation Framework -- Automated Intervertebral Disc Segmentation Using Probabilistic Shape Estimation and Active Shape Models. . |
| Record Nr. | UNISA-996465678203316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : 4th International Workshop and Challenge, CSI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected Papers / / edited by Jianhua Yao, Tomaž Vrtovec, Guoyan Zheng, Alejandro Frangi, Ben Glocker, Shuo Li
| Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : 4th International Workshop and Challenge, CSI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected Papers / / edited by Jianhua Yao, Tomaž Vrtovec, Guoyan Zheng, Alejandro Frangi, Ben Glocker, Shuo Li |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (X, 147 p. 60 illus.) |
| Disciplina | 006.37 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Computer graphics Artificial intelligence Computer simulation Algorithms Image Processing and Computer Vision Pattern Recognition Computer Graphics Artificial Intelligence Simulation and Modeling Algorithm Analysis and Problem Complexity |
| ISBN | 3-319-55050-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | State-of-the-art techniques -- Novel and emerging analysis and visualization techniques -- Clinical challenges and open problems -- Major aspects of problems related to spine imaging -- Including clinical applications of spine imaging -- Computer aided diagnosis of spine conditions -- Computer aided detection of spine-related diseases -- Emerging computational imaging techniques for spinal diseases,.-Fast 3D reconstruction of spine, feature extraction, multiscale analysis, pattern recognition, image enhancement of spine imaging -- Image-guided spine intervention and treatment, multimodal image registration and fusion for spine imaging -- Novel visualization techniques, segmentation techniques for spine imaging, statistical and geometric modeling for spine and vertebra, spine and vertebra localization. |
| Record Nr. | UNISA-996466086603316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Computational Methods and Clinical Applications in Musculoskeletal Imaging [[electronic resource] ] : 6th International Workshop, MSKI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers / / edited by Tomaž Vrtovec, Jianhua Yao, Guoyan Zheng, Jose M. Pozo
| Computational Methods and Clinical Applications in Musculoskeletal Imaging [[electronic resource] ] : 6th International Workshop, MSKI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers / / edited by Tomaž Vrtovec, Jianhua Yao, Guoyan Zheng, Jose M. Pozo |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XII, 153 p. 74 illus., 63 illus. in color.) |
| Disciplina | 616.70754 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Health informatics Image Processing and Computer Vision Artificial Intelligence Health Informatics |
| ISBN | 3-030-11166-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Automated Recognition of Erector Spinae Muscles and Their Skeletal Attachment Region via Deep Learning in Torso CT Images -- Fully automatic teeth segmentation in adult OPG images -- Fully Automatic Planning of Total Shoulder Arthroplasty without Segmentation: A Deep Learning Based Approach -- Deep Volumetric Shape Learning for Semantic Segmentation of the Hip Joint from 3D MR Images -- Pelvis segmentation using multi-pass U-net and iterative shape estimation -- Bone Adaptation as Level Set Motion -- Landmark Localisation in Radiographs Using Weighted Heatmap Displacement Voting -- Perthes Disease Classification Using Shape and Appearance Modelling -- Deep Learning Based Rib Centerline Extraction and Labeling -- Automatic Wrist Fracture Detection From Posteroanterior and Lateral Radiographs: A Deep Learning-Based Approach -- Bone Reconstruction and Depth Control During Laser Ablation -- Automated Dynamic 3D Ultrasound Assessment of Developmental Dysplasia of the Infant Hip -- Automated Measurement of Pelvic Incidence from X-Ray Images. |
| Record Nr. | UNINA-9910337566403321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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