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 | ||
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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 for Spine Imaging : 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 |
Computer vision
Pattern recognition systems Computer graphics Artificial intelligence Computer simulation Algorithms Computer Vision Automated Pattern Recognition Computer Graphics Artificial Intelligence Computer Modelling |
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 | ||
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Computational Methods and Clinical Applications for Spine Imaging : 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 |
Computer vision
Pattern recognition systems Computer graphics Artificial intelligence Computer simulation Algorithms Computer Vision Automated Pattern Recognition Computer Graphics Artificial Intelligence Computer Modelling |
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 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. | UNISA-996466452603316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Computational Methods and Clinical Applications in Musculoskeletal Imaging : 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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Computational Methods and Clinical Applications in Musculoskeletal Imaging [[electronic resource] ] : 5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers / / edited by Ben Glocker, Jianhua Yao, Tomaž Vrtovec, Alejandro Frangi, Guoyan Zheng |
Edizione | [1st ed. 2018.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
Descrizione fisica | 1 online resource (XII, 161 p. 71 illus.) |
Disciplina | 616.70754 |
Collana | Computer Communication Networks and Telecommunications |
Soggetto topico |
Optical data processing
Artificial intelligence Computer communication systems Image Processing and Computer Vision Artificial Intelligence Computer Communication Networks |
ISBN | 3-319-74113-6 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Localization of Bone Surfaces from Ultrasound Data Using Local Phase Information and Signal Transmission Maps -- Shape-aware Deep Convolutional Neural Network for Vertebrae Segmentation -- Automated Characterization of Body Composition and Frailty with Clinically Acquired CT -- Unfolded cylindrical projection for rib fracture diagnosis -- 3D Cobb Angle Measurements from Scoliotic Mesh Models with Varying Face-Vertex Density -- Automatic Localization of the Lumbar Vertebral Landmarks in CT Images with Context Features -- Joint Multimodal Segmentation of Clinical CT and MR from Hip Arthroplasty Patients -- Reconstruction of 3D muscle fiber structure using high resolution cryosectioned volume -- Segmentation of Pathological Spines in CT Images Using a Two-Way CNN and a Collision-Based Model -- Attention-driven deep learning for pathological spine segmentation -- Automatic Full Femur Segmentation from Computed Tomography Datasets using an Atlas-Based Approach -- Classification of Osteoporotic Vertebral Fractures using Shape and Appearance Modelling -- DSMS-FCN: A Deeply Supervised Multi-Scale Fully Convolutional Network for Automatic Segmentation of Intervertebral Disc in 3D MR Images. |
Record Nr. | UNISA-996465480803316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Computational Methods and Clinical Applications in Musculoskeletal Imaging : 5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers / / edited by Ben Glocker, Jianhua Yao, Tomaž Vrtovec, Alejandro Frangi, Guoyan Zheng |
Edizione | [1st ed. 2018.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
Descrizione fisica | 1 online resource (XII, 161 p. 71 illus.) |
Disciplina | 616.70754 |
Collana | Computer Communication Networks and Telecommunications |
Soggetto topico |
Computer vision
Artificial intelligence Computer networks Computer Vision Artificial Intelligence Computer Communication Networks |
ISBN | 3-319-74113-6 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Localization of Bone Surfaces from Ultrasound Data Using Local Phase Information and Signal Transmission Maps -- Shape-aware Deep Convolutional Neural Network for Vertebrae Segmentation -- Automated Characterization of Body Composition and Frailty with Clinically Acquired CT -- Unfolded cylindrical projection for rib fracture diagnosis -- 3D Cobb Angle Measurements from Scoliotic Mesh Models with Varying Face-Vertex Density -- Automatic Localization of the Lumbar Vertebral Landmarks in CT Images with Context Features -- Joint Multimodal Segmentation of Clinical CT and MR from Hip Arthroplasty Patients -- Reconstruction of 3D muscle fiber structure using high resolution cryosectioned volume -- Segmentation of Pathological Spines in CT Images Using a Two-Way CNN and a Collision-Based Model -- Attention-driven deep learning for pathological spine segmentation -- Automatic Full Femur Segmentation from Computed Tomography Datasets using an Atlas-Based Approach -- Classification of Osteoporotic Vertebral Fractures using Shape and Appearance Modelling -- DSMS-FCN: A Deeply Supervised Multi-Scale Fully Convolutional Network for Automatic Segmentation of Intervertebral Disc in 3D MR Images. |
Record Nr. | UNINA-9910349261903321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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