LEADER 02815oam 2200625M 450 001 9910717353503321 005 20191123062012.6 035 $a(MiFhGG)INDP000397 035 $a(CKB)4920000002508656 035 $a(OCoLC)1065605743 035 $a(OCoLC)994920000002508656 035 $a(EXLCZ)994920000002508656 100 $a20070221d1850 ua 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRoute from Fort Smith to Santa Fe. Letter from the Secretary of War, transmitting, in compliance with a resolution of the House of the 6th February, a report and map of Lieutenant Simpson, of the route from Fort Smith to Santa Fe ; also, a report on the same subject from Captain R.B. Marcy, 5th infantry. February 21, 1850. Referred to the Committee on Military Affairs, and ordered to be printed 210 1$a[Washington, D.C.] :$c[publisher not identified],$d1850. 215 $a1 online resource (89 pages) $cillustrations, maps, tables 225 1 $aEx. doc. / 31st Congress, 1st session. House ;$vno. 45 225 1 $a[United States congressional serial set ] ;$v[serial no. 577] 300 $aBatch processed record: Metadata reviewed, not verified. Some fields updated by batch processes. 300 $aFDLP item number not assigned. 517 $aRoute from Fort Smith to Santa Fe 606 $aDiscoveries in geography 606 $aIndians of North America$xGovernment relations 606 $aGeography 606 $aSurveying 606 $aTrails 606 $aMigration, Internal$zWest (U.S.) 606 $aIndians 606 $aDescription and travel 608 $aLegislative materials.$2lcgft 615 0$aDiscoveries in geography. 615 0$aIndians of North America$xGovernment relations. 615 0$aGeography. 615 0$aSurveying. 615 0$aTrails. 615 0$aMigration, Internal 615 0$aIndians. 615 0$aDescription and travel. 701 $aMarcy$b Randolph Barnes$01407430 701 $aSimpson$b J. H$g(James Hervey),$f1813-1883.$01397397 712 02$aUnited States.$bWar Department. 712 02$aUnited States.$bTopographical Bureau. 801 0$bWYU 801 1$bWYU 801 2$bOCLCO 801 2$bOCLCQ 906 $aBOOK 912 $a9910717353503321 996 $aRoute from Fort Smith to Santa Fe. Letter from the Secretary of War, transmitting, in compliance with a resolution of the House of the 6th February, a report and map of Lieutenant Simpson, of the route from Fort Smith to Santa Fe ; also, a report on the same subject from Captain R.B. Marcy, 5th infantry. February 21, 1850. Referred to the Committee on Military Affairs, and ordered to be printed$93533264 997 $aUNINA LEADER 05929nam 22007815 450 001 9910349404603321 005 20251225203455.0 010 $a9783030008079 010 $a303000807X 024 7 $a10.1007/978-3-030-00807-9 035 $a(CKB)4100000006674713 035 $a(DE-He213)978-3-030-00807-9 035 $a(MiAaPQ)EBC6280959 035 $a(PPN)230538827 035 $a(EXLCZ)994100000006674713 100 $a20180914d2018 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData Driven Treatment Response Assessment and Preterm, Perinatal, and Paediatric Image Analysis $eFirst International Workshop, DATRA 2018 and Third International Workshop, PIPPI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings /$fedited by Andrew Melbourne, Roxane Licandro, Matthew DiFranco, Paolo Rota, Melanie Gau, Martin Kampel, Rosalind Aughwane, Pim Moeskops, Ernst Schwartz, Emma Robinson, Antonios Makropoulos 205 $a1st ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (XI, 180 p. 74 illus.) 225 1 $aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v11076 300 $aIncludes index. 311 08$a9783030008062 311 08$a3030008061 327 $aDeepCS: Deep Convolutional Neural Network and SVM based Single Image Super-Resolution -- Automatic Segmentation of Thigh Muscle in Longitudinal 3D T1-Weighted Magnetic Resonance (MR) Images -- Detecting Bone Lesions in Multiple Myeloma Patient Using Transfer Learning -- Quantification of Local Metabolic Tumor Volume Changes by Registering Blended PET-CT Images for Prediction of Pathologic Tumor Response -- Optimizing External Surface Sensor Locations for Respiratory Tumor Motion Prediction -- Segmentation of Fetal Adipose Tissue Using Efficient CNNs for Portable Ultrasound -- Automatic Shadow Detection in 2D Ultrasound Images -- Multi-Channel Groupwise Registration to Construct and Ultrasound-Specific Fetal Brain Atlas -- Investigating Brain Age Deviation in Preterm Infants: A Deep Learning Approach -- Segmentation of Pelvic Vessels in Pediatric MRI Using a Patch-Based Deep Learning Approach -- Multi-View Image Reconstruction: Application to Fetal Ultrasound Compounding -- EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging Without External Trackers -- Better Feature Matching for Placental Panorama Construction -- Combining Deep Learning and Multi-Atlas Label Fusion for Automated Placenta Segmentation from 3DUS -- LSTM Spatial Co-transformer Networks for Registration of 3D Fetal US and MR Brain Images -- Automatic and Efficient Standard Plane Recognition in Fetal Ultrasound Images via Multi-Scale Dense Networks -- Paediatric Liver Segmentation for Low-Contrast CT Images. 330 $aThis book constitutes the refereed joint proceedings of the First International Workshop on Data Driven Treatment Response Assessment, DATRA 2018 and the Third International Workshop on Preterm, Perinatal and Paediatric Image Analysis, PIPPI 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 5 full papers presented at DATRA 2018 and the 12 full papers presented at PIPPI 2018 were carefully reviewed and selected. The DATRA papers cover a wide range of exploring pattern recognition technologies for tackling clinical issues related to the follow-up analysis of medical data with focus on malignancy progression analysis, computer-aided models of treatment response, and anomaly detection in recovery feedback. The PIPPI papers cover topics of advanced image analysis approaches focused on the analysis of growth and development in the fetal, infantand paediatric period. 410 0$aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v11076 606 $aArtificial intelligence 606 $aComputer vision 606 $aMedical informatics 606 $aComputer arithmetic and logic units 606 $aArtificial Intelligence 606 $aComputer Vision 606 $aHealth Informatics 606 $aArithmetic and Logic Structures 615 0$aArtificial intelligence. 615 0$aComputer vision. 615 0$aMedical informatics. 615 0$aComputer arithmetic and logic units. 615 14$aArtificial Intelligence. 615 24$aComputer Vision. 615 24$aHealth Informatics. 615 24$aArithmetic and Logic Structures. 676 $a616.07540285 676 $a616.0757 702 $aMelbourne$b Andrew$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLicandro$b Roxane$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aDiFranco$b Matthew$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRota$b Paolo$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGau$b Melanie$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKampel$b Martin$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aAughwane$b Rosalind$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMoeskops$b Pim$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSchwartz$b Ernst$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRobinson$b Emma$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMakropoulos$b Antonios$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910349404603321 996 $aData Driven Treatment Response Assessment and Preterm, Perinatal, and Paediatric Image Analysis$92263618 997 $aUNINA