LEADER 06781nam 22006975 450 001 9910299753603321 005 20200630232025.0 010 $a3-319-07269-2 024 7 $a10.1007/978-3-319-07269-2 035 $a(CKB)3710000000187226 035 $a(EBL)1783031 035 $a(OCoLC)894170110 035 $a(SSID)ssj0001295616 035 $a(PQKBManifestationID)11780914 035 $a(PQKBTitleCode)TC0001295616 035 $a(PQKBWorkID)11342655 035 $a(PQKB)10116536 035 $a(MiAaPQ)EBC1783031 035 $a(DE-He213)978-3-319-07269-2 035 $a(PPN)179924109 035 $a(EXLCZ)993710000000187226 100 $a20140711d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aComputational Methods and Clinical Applications for Spine Imaging$b[electronic resource] $eProceedings of the Workshop held at the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, September 22-26, 2013, Nagoya, Japan /$fedited by Jianhua Yao, Tobias Klinder, Shuo Li 205 $a1st ed. 2014. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014. 215 $a1 online resource (229 p.) 225 1 $aLecture Notes in Computational Vision and Biomechanics,$x2212-9391 ;$v17 300 $aDescription based upon print version of record. 311 $a3-319-07268-4 320 $aIncludes bibliographical references at the end of each chapters. 327 $aPreface -- 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, Toma? 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 Toma? 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. 330 $aThis book contains the full papers presented at the MICCAI 2013 workshop Computational Methods and Clinical Applications for Spine Imaging. The workshop brought together researchers representing several fields, such as Biomechanics, Engineering, Medicine, Mathematics, Physics and Statistic. The works included in this book present and discuss new trends in those fields, using several methods and techniques in order to address more efficiently different and timely applications involving signal and image acquisition, image processing and analysis, image segmentation, image registration and fusion, computer simulation, image based modelling, simulation and surgical planning, image guided robot assisted surgical and image based diagnosis. 410 0$aLecture Notes in Computational Vision and Biomechanics,$x2212-9391 ;$v17 606 $aBiomedical engineering 606 $aOptical data processing 606 $aRadiology 606 $aBiomedical Engineering and Bioengineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T2700X 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22005 606 $aImaging / Radiology$3https://scigraph.springernature.com/ontologies/product-market-codes/H29005 615 0$aBiomedical engineering. 615 0$aOptical data processing. 615 0$aRadiology. 615 14$aBiomedical Engineering and Bioengineering. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aImaging / Radiology. 676 $a616.730754 702 $aYao$b Jianhua$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKlinder$b Tobias$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLi$b Shuo$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299753603321 996 $aComputational Methods and Clinical Applications for Spine Imaging$91959956 997 $aUNINA