05026nam 22007095 450 99641820560331620200701035544.03-030-39752-110.1007/978-3-030-39752-4(CKB)4100000010121601(DE-He213)978-3-030-39752-4(MiAaPQ)EBC6114115(PPN)242845118(EXLCZ)99410000001012160120200131d2020 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierComputational 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 Li1st ed. 2020.Cham :Springer International Publishing :Imprint: Springer,2020.1 online resource (XII, 120 p. 63 illus., 50 illus. in color.) Image Processing, Computer Vision, Pattern Recognition, and Graphics ;119633-030-39751-3 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.This book constitutes the proceedings of the 7th International Workshop and Challenge on Computational Methods and Clinical Applications for Spine Imaging, CSI 2019, which was held in conjunction with MICCAI on October 17, 2019, in Shenzhen, China. All submissions were accepted for publication; the book contains 5 peer-reviewed regular papers, covering topics of vertrebra detection, spine segmentation and image-based diagnosis, and 9 challenge papers, investigating (semi-)automatic spinal curvature estimation algorithms and providing a standard evaluation framework with a set of x-ray images. .Image Processing, Computer Vision, Pattern Recognition, and Graphics ;11963Optical data processingMachine learningComputersEducation—Data processingApplication softwareImage Processing and Computer Visionhttps://scigraph.springernature.com/ontologies/product-market-codes/I22021Machine Learninghttps://scigraph.springernature.com/ontologies/product-market-codes/I21010Information Systems and Communication Servicehttps://scigraph.springernature.com/ontologies/product-market-codes/I18008Computers and Educationhttps://scigraph.springernature.com/ontologies/product-market-codes/I24032Computer Appl. in Social and Behavioral Scienceshttps://scigraph.springernature.com/ontologies/product-market-codes/I23028Optical 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.616.730754Cai Yunliangedthttp://id.loc.gov/vocabulary/relators/edtWang Lianshengedthttp://id.loc.gov/vocabulary/relators/edtAudette Micheledthttp://id.loc.gov/vocabulary/relators/edtZheng Guoyanedthttp://id.loc.gov/vocabulary/relators/edtLi Shuoedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK996418205603316Computational Methods and Clinical Applications for Spine Imaging1959956UNISA