LEADER 05257 am 22006613u 450 001 9910220007403321 005 20200705024554.0 010 $a3-319-49644-1 024 7 $a10.1007/978-3-319-49644-3 035 $a(CKB)4340000000062217 035 $a(DE-He213)978-3-319-49644-3 035 $a(MiAaPQ)EBC5610360 035 $a(Au-PeEL)EBL5610360 035 $a(OCoLC)1073090964 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/61975 035 $a(PPN)201473941 035 $a(EXLCZ)994340000000062217 100 $a20170517d2017 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aCloud-Based Benchmarking of Medical Image Analysis$b[electronic resource] /$fedited by Allan Hanbury, Henning Müller, Georg Langs 205 $a1st ed. 2017. 210 $cSpringer Nature$d2017 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017. 215 $a1 online resource (XVIII, 254 p. 93 illus., 39 illus. in color.) 311 $a3-319-49642-5 327 $aVISCERAL: Evaluation-as-a-Service for Medical Imaging -- Using the Cloud as a Platform for Evaluation and Data Preparation -- Ethical and Privacy Aspects of Using Medical Image Data -- Annotating Medical Image Data -- Datasets created in VISCERAL -- Evaluation Metrics for Medical Organ Segmentation and Lesion Detection -- VISCERAL Anatomy Benchmarks for Organ Segmentation and Landmark Localisation: Tasks and Results -- Retrieval of Medical Cases for Diagnostic Decisions: VISCERAL Retrieval Benchmark -- Automatic Atlas-Free Multi-Organ Segmentation of Contrast-Enhanced CT Scans -- Multi-organ Segmentation Using Coherent Propagating Level Set Method Guided by Hierarchical Shape Priors and Local Phase Information -- Automatic Multi-organ Segmentation using Hierarchically-Registered Probabilistic Atlases -- Multi-Atlas Segmentation Using Robust Feature-Based Registration -- Combining Radiology Images and Clinical Meta-data for Multimodal Medical Case-based Retrieval -- Text and Content-based Medical Image Retrieval in the VISCERAL Retrieval Benchmark. 330 $aThis book is open access under a CC BY-NC 2.5 license. This book presents the VISCERAL project benchmarks for analysis and retrieval of 3D medical images (CT and MRI) on a large scale, which used an innovative cloud-based evaluation approach where the image data were stored centrally on a cloud infrastructure and participants placed their programs in virtual machines on the cloud. The book presents the points of view of both the organizers of the VISCERAL benchmarks and the participants. The book is divided into five parts. Part I presents the cloud-based benchmarking and Evaluation-as-a-Service paradigm that the VISCERAL benchmarks used. Part II focuses on the datasets of medical images annotated with ground truth created in VISCERAL that continue to be available for research. It also covers the practical aspects of obtaining permission to use medical data and manually annotating 3D medical images efficiently and effectively. The VISCERAL benchmarks are described in Part III, including a presentation and analysis of metrics used in evaluation of medical image analysis and search. Lastly, Parts IV and V present reports by some of the participants in the VISCERAL benchmarks, with Part IV devoted to the anatomy benchmarks and Part V to the retrieval benchmark. This book has two main audiences: the datasets as well as the segmentation and retrieval results are of most interest to medical imaging researchers, while eScience and computational science experts benefit from the insights into using the Evaluation-as-a-Service paradigm for evaluation and benchmarking on huge amounts of data. 606 $aHealth informatics 606 $aOptical data processing 606 $aComputer system failures 606 $aHealth Informatics$3https://scigraph.springernature.com/ontologies/product-market-codes/I23060 606 $aHealth Informatics$3https://scigraph.springernature.com/ontologies/product-market-codes/H28009 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 606 $aSystem Performance and Evaluation$3https://scigraph.springernature.com/ontologies/product-market-codes/I13049 610 $aMedical imaging 615 0$aHealth informatics. 615 0$aOptical data processing. 615 0$aComputer system failures. 615 14$aHealth Informatics. 615 24$aHealth Informatics. 615 24$aImage Processing and Computer Vision. 615 24$aSystem Performance and Evaluation. 676 $a502.85 700 $aGeorg Langs$4auth$01355568 702 $aHanbury$b Allan$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMüller$b Henning$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLangs$b Georg$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910220007403321 996 $aCloud-Based Benchmarking of Medical Image Analysis$93359712 997 $aUNINA LEADER 01333nam a2200337 i 4500 001 991000952999707536 005 20020507180508.0 008 950626s1980 us ||| | eng 020 $a3764330236 035 $ab1078052x-39ule_inst 035 $aLE01304807$9ExL 040 $aDip.to Matematica$beng 082 0 $a510.89 084 $aAMS 01A55 084 $aAMS 53-03 084 $aQA613 100 1 $aScholz, Erhard$067007 245 10$aGeschichte des Mannigfaltigkeitsbegriffs von Riemann bis Poincare /$cErhard Scholz 260 $aBoston :$bBirkhauser,$c1980 300 $a430 p., [1] leaf of plates :$bill. ;$c23 cm. 500 $aBibliography: p. 408-430. 500 $aOriginally presented as the author's thesis (doctoral Bonn, 1979) under the title: Entwicklung des Mannigfaltigkeitsbegriffs von Riemann bis Poincare 650 4$aDifferential geometry-history 650 4$aHistory of mathematics-19th century 650 4$aManifolds-history 907 $a.b1078052x$b21-09-06$c28-06-02 912 $a991000952999707536 945 $aLE013 01A SCH11 (1980)$g1$i2013000031323$lle013$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i10880100$z28-06-02 996 $aGeschichte des Mannigfaltigkeitsbegriffs von Riemann bis Poincare$9921875 997 $aUNISALENTO 998 $ale013$b01-01-95$cm$da $e-$feng$gus $h0$i1