LEADER 02290oam 2200517 450 001 9910707759703321 005 20170501081745.0 035 $a(CKB)5470000002466951 035 $a(OCoLC)962070632 035 $a(EXLCZ)995470000002466951 100 $a20161104d2016 ua 0 101 0 $aeng 135 $aurbn||||a|||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aImproving college access and completion for low-income and first-generation students $ehearing before the Subcommittee on Higher Education and Workforce Training, Committee on Education and the Workforce, House of Representatives, One Hundred Fourteenth Congress, first session, hearing held in Washington, DC, April 30, 2015 210 1$aWashington :$cU.S. Government Publishing Office,$d2016. 215 $a1 online resource (iii, 69 pages) 300 $aPaper version available for sale by the Superintendent of Documents, United States Government Publishing Office. 300 $a"Serial no. 114-13." 320 $aIncludes bibliographical references. 517 $aImproving college access and completion for low-income and first-generation students 606 $aLow-income college students$xServices for$zUnited States 606 $aFirst-generation college students$xServices for$zUnited States 606 $aFederal aid to higher education$zUnited States 606 $aCounseling in higher education$zUnited States 606 $aAcademic achievement$xGovernment policy$zUnited States 606 $aCollege dropouts$xPrevention$xGovernment policy$zUnited States 608 $aLegislative hearings.$2lcgft 615 0$aLow-income college students$xServices for 615 0$aFirst-generation college students$xServices for 615 0$aFederal aid to higher education 615 0$aCounseling in higher education 615 0$aAcademic achievement$xGovernment policy 615 0$aCollege dropouts$xPrevention$xGovernment policy 801 0$bGPO 801 1$bGPO 801 2$bGPO 801 2$bCUT 801 2$bAZP 801 2$bGPO 906 $aBOOK 912 $a9910707759703321 996 $aImproving college access and completion for low-income and first-generation students$93535969 997 $aUNINA LEADER 04636nam 22007215 450 001 9910373927703321 005 20251113184342.0 010 $a3-030-39752-1 024 7 $a10.1007/978-3-030-39752-4 035 $a(CKB)4100000010121601 035 $a(DE-He213)978-3-030-39752-4 035 $a(MiAaPQ)EBC6114115 035 $a(PPN)242845118 035 $a(EXLCZ)994100000010121601 100 $a20200131d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputational Methods and Clinical Applications for Spine Imaging $e6th International Workshop and Challenge, CSI 2019, Shenzhen, China, October 17, 2019, Proceedings /$fedited by Yunliang Cai, Liansheng Wang, Michel Audette, Guoyan Zheng, Shuo Li 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (XII, 120 p. 63 illus., 50 illus. in color.) 225 1 $aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v11963 311 08$a3-030-39751-3 327 $aRegular 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. 330 $aThis book constitutes the proceedings of the 7th International Workshop and Challenge on Computational Methods and Clinical Applications for Spine Imaging, CSI 2019, which was held in conjunction with MICCAI on October 17, 2019, in Shenzhen, China. All submissions were accepted for publication; the book contains 5 peer-reviewed regular papers, covering topics of vertrebra detection, spine segmentation and image-based diagnosis, and 9 challenge papers, investigating (semi-)automatic spinal curvature estimation algorithms and providing a standard evaluation framework with a set of x-ray images. . 410 0$aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v11963 606 $aComputer vision 606 $aMachine learning 606 $aComputer networks 606 $aEducation$xData processing 606 $aSocial sciences$xData processing 606 $aComputer Vision 606 $aMachine Learning 606 $aComputer Communication Networks 606 $aComputers and Education 606 $aComputer Application in Social and Behavioral Sciences 615 0$aComputer vision. 615 0$aMachine learning. 615 0$aComputer networks. 615 0$aEducation$xData processing. 615 0$aSocial sciences$xData processing. 615 14$aComputer Vision. 615 24$aMachine Learning. 615 24$aComputer Communication Networks. 615 24$aComputers and Education. 615 24$aComputer Application in Social and Behavioral Sciences. 676 $a616.730754 676 $a616.730754 702 $aCai$b Yunliang$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWang$b Liansheng$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aAudette$b Michel$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aZheng$b Guoyan$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 $a9910373927703321 996 $aComputational Methods and Clinical Applications for Spine Imaging$91959956 997 $aUNINA