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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
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
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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
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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
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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
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
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Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : Proceedings of the Workshop held at the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, September 22-26, 2013, Nagoya, Japan / / edited by Jianhua Yao, Tobias Klinder, Shuo Li
Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] ] : Proceedings of the Workshop held at the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, September 22-26, 2013, Nagoya, Japan / / edited by Jianhua Yao, Tobias Klinder, Shuo Li
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (229 p.)
Disciplina 616.730754
Collana Lecture Notes in Computational Vision and Biomechanics
Soggetto topico Biomedical engineering
Optical data processing
Radiology
Biomedical Engineering and Bioengineering
Computer Imaging, Vision, Pattern Recognition and Graphics
Imaging / Radiology
ISBN 3-319-07269-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface -- Workshop Organization -- Segmentation I (CT): Segmentation of vertebrae from 3D spine images by applying concepts from transportation and game theories, by Bulat Ibragimov, Bostjan Likar, Franjo Pernus, Tomaž Vrtovec -- Automatic and Reliable Segmentation of Spinal Canals in Low-Resolution, Low-Contrast CT Images, by Qian Wang, Le Lu, Diji Wu, Noha El-Zehiry, Dinggang Shen, Kevin Zhou -- A Robust Segmentation Framework for Spine Trauma Diagnosis, by Poay Hoon Lim, Ulas Bagci, Li Bai -- 2D-PCA based Tensor Level Set Framework for Vertebral Body Segmentation, by Ahmed Shalaby, Aly Farag, Melih Aslan -- Computer Aided Detection and Diagnosis: Computer Aided Detection of Spinal Degenerative Osteophytes on Sodium Fluoride PET/CT, by Jianhua Yao, Hector Munoz , Joseph Burns, Le Lu, Ronald Summers -- Novel Morphological and Appearance Features for Predicting Physical Disability from MR Images in Multiple Sclerosis Patients, by Jeremy Kawahara, Chris McIntosh, Roger Tam, Ghassan Hamarneh -- Classification of Spinal Deformities using a Parametric Torsion Estimator, by Jesse Shen, Stefan Parent, Samuel Kadoury -- Lumbar Spine Disc Herniation Diagnosis with a Joint Shape Model, by Raja Alomari, Vipin Chaudhary, Jason Corso, Gurmeet Dhillon -- Epidural Masses Detection on Computed Tomography Using Spatially-Constrained Gaussian Mixture Models, by Sanket Pattanaik, Jiamin Liu, Jianhua Yao, Weidong Zhang, Evrim Turkbey, Xiao Zhang, Ronald Summers -- Quantitative Imaging: Comparison of manual and computerized measurements of sagittal vertebral inclination in MR images, by Tomaž Vrtovec, Franjo Pernus, Bostjan Likar -- Eigenspine: Eigenvector Analysis of Spinal Deformities in Idiopathic Scoliosis, by Daniel Forsberg, Claes Lundström, Mats Andersson, Hans Knutsson -- Quantitative Monitoring of Syndesmophyte Growth in Ankylosing Spondylitis Using Computed Tomography, by Sovira Tan, Jianhua Yao, Lawrence Yao, Michael Ward -- A Semi-automatic Method for the Quantification of Spinal Cord Atrophy, by Simon Pezold, Michael Amann, Katrin Weier, Ketut Fundana, Ernst Radue, Till Sprenger, Philippe Cattin -- Segmentation II (MR): Multi-modal vertebra segmentation from MR Dixon in hybrid whole-body PET/MR, by Christian Buerger, Jochen Peters, Irina Waechter-Stehle, Frank Weber, Tobias Klinder, Steffen Renisch -- Segmentation of intervertebral discs from high-resolution 3D MRI using multi-level statistical shape models, by Ales Neubert, Jurgen Fripp, Craig Engstrom, Stuart Crozier -- A supervised approach towards segmentation of clinical MRI for automatic lumbar diagnosis, by Subarna Ghosh, Manavender Malgireddy, Vipin Chaudhary, Gurmeet Dhillon -- Registration/Labeling: Automatic Segmentation and Discrimination of Connected Joint Bones from CT by Multi-atlas Registration, by Tristan Whitmarsh, Graham Treece, Kenneth Poole -- Registration of MR to Percutaneous Ultrasound of the Spine for Image-Guided Surgery, by Lars Eirik Bø, Rafael Palomar, Tormod Selbekk, Ingerid Reinertsen -- Vertebrae Detection and Labelling in Lumbar MR Images, by Meelis Lootus, Timor Kadir, Andrew Zisserman.
Record Nr. UNINA-9910299753603321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
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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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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. UNISA-996466452603316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019
Materiale a stampa
Lo trovi qui: Univ. di Salerno
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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
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
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Lo trovi qui: Univ. di Salerno
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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
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. UNINA-9910349261903321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Recent Advances in Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] /] / edited by Jianhua Yao, Ben Glocker, Tobias Klinder, Shuo Li
Recent Advances in Computational Methods and Clinical Applications for Spine Imaging [[electronic resource] /] / edited by Jianhua Yao, Ben Glocker, Tobias Klinder, Shuo Li
Edizione [1st ed. 2015.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
Descrizione fisica 1 online resource (259 p.)
Disciplina 616.0754
Collana Lecture Notes in Computational Vision and Biomechanics
Soggetto topico Biomedical engineering
Radiology
Signal processing
Image processing
Speech processing systems
Mathematics
Medical physics
Radiation
Biomedical Engineering and Bioengineering
Imaging / Radiology
Signal, Image and Speech Processing
Mathematics, general
Medical and Radiation Physics
ISBN 3-319-14148-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface -- Workshop Organization -- Computer Aided Diagnosis and Intervention -- Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications, by Holger Roth, Jianhua Yao, Le, James Stieger, Joseph Burns, Ronald Summers -- Stacked auto-encoders for classification of 3D spine models in adolescent idiopathic scoliosis, by William Thong, Hubert Labelle, Jesse Shen, Stefan Parent, Samuel Kadoury -- An Active Optical Flow Model for Dose Prediction in Spinal SBRT Plans, by Jianfei Liu, Jackie Wu, FangFang Yin, John Kirkpatrick, Alvin Cabrera, Yaorong Ge -- Portable optically tracked ultrasound system for scoliosis measurement, by Guillermo Carbajal, Álvaro Gómez, Gabor Fichtinger, Tamas Ungi -- Spine Segmentation -- Atlas-Based Registration for Accurate Segmentation of Thoracic and Lumbar Vertebrae in CT Data, by Daniel Forsberg -- Segmentation of Lumbar Vertebrae Slices from CT Images, by Hugo Hutt, Richard Everson, Judith Meakin -- Interpolation-Based Detection of Lumbar Vertebrae in CT Spine Images, by Bulat Ibragimov, Robert Korez, Bostjan Likar, Franjo Pernus, Tomaz Vrtovec -- An Improved Shape-Constrained Deformable Model for Segmentation of Vertebrae from CT Lumbar Spine Images, by Robert Korez, Bulat Ibragimov, Bostjan Likar, Franjo Pernus, Tomaz Vrtovec -- Detailed Vertebral Segmentation using Part-Based Decomposition and Conditional Shape Models, by Marco Pereañez, Karim Lekadir, Corné Hoogendoorn, Isaac Castro Mateos, Alejandro Frangi -- MR Image Processing -- Automatic Segmentation of the Spinal Cord using Continuous Max Flow with Cross-sectional Similarity Prior and Tubularity Features, by Simon Pezold, Ketut Fundana, Michael Amann, Michaela Andelova, Armanda Pfister, Till Sprenger, Philippe Cattin -- Automated Radiological Measurement of Spinal MRI, by Meelis Lootus, Timor Kadir, Andrew Zisserman --  Automated 3D Lumbar Intervertebral Disc Segmentation from MRI Images,  by Xiao Dong, Guoyan Zheng -- Minimally Supervised Segmentation and Meshing of 3D Intervertebral Discs of the Lumbar Spine for Discectomy Simulation, by Rabia Haq, Rifat Aras, Roderick Borgie, David Besachio, Michel Audette --  Localization --  Localisation of Vertebrae on DXA Images using Constrained Local Models with Random Forest Regression Voting, by Paul Bromiley, Judith Adams, Tim Cootes -- Bone Profiles: Simple, Fast, and Reliable Spine Localization in CT Scans, by Jiri Hladuvka, David Major, Katja Bühler -- Modeling -- Area- and Angle-preserving Parametrization for Vertebra Surface Mesh, by Shoko Miyauchi, Ken'ichi Morooka, Tokuo Tsuji, Yasushi Miyagi, Takaichi Fukuda, Ryo Kurazame -- Contour models for descriptive patient-specific neuro-anatomical modeling: towards a digital brainstem atlas, by Nirmal Patel, Sharmin Sultana, Michel Audette -- Segmentation Challenge -- Atlas-Based Segmentation of the Thoracic and Lumbar Vertebrae, by Daniel Forsberg -- Lumbar and thoracic spine segmentation using a statistical multi-object shape+pose model,  by Alexander Seitel, Abtin Rasoulian, Robert Rohling, Purang Abolmaesumi -- Vertebrae Segmentation in 3D CT Images based on a Variational Framework,  by Kerstin Hammernik, Thomas Ebner, Darko Stern, Martin Urschler, Thomas Pock -- Interpolation-Based Shape-Constrained Deformable Model Approach for Segmentation of Vertebrae from CT Spine Images,  by Robert Korez, Bulat Ibragimov, Bostjan Likar, Franjo, Tomaz Vrtovec -- 3D Vertebra segmentation by feature selection Active Shape Model, by Isaac Castro Mateos, Jose Pozo Soler, Alejandro Frangi -- Report of Vertebra Segmentation Challenge in 2014 MICCAI Workshop on Computational Spine Imaging, by Jianhua Yao,  Shuo Li.
Record Nr. UNINA-9910299700203321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
Materiale a stampa
Lo trovi qui: Univ. Federico II
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