01091cam0-2200325---450 99000991393040332120210526103543.0000991393FED01000991393(Aleph)000991393FED0100099139320141106d1860----km-y0itay50------bafreFRy-------001yy<<L'>>Italie est-elle la terre des morts?par Marc-MonnierParisL. Hachette et C.1860434 p.19 cmItaliaCulturaSec. 18.-19.Ed. ante 1900306.094594519itaMonnier,Marc<1827-1885>39292ITUNINARICAUNIMARCVisualizza la versione elettronica in SBNWebhttps://books.google.it/books?id=T4-xqp86Q8AC&printsec=frontcover&hl=it&source=gbs_ge_summary_r&cad=0#v=onepage&q&f=false20210526BK990009913930403321SG 300/A 102R.Bibl. 11075FLFBCFLFBCItalie est-elle La terre des morts831210UNINA06336nam 22008175 450 991048469290332120251226203953.03-540-46258-910.1007/11889762(CKB)1000000000283783(SSID)ssj0000316925(PQKBManifestationID)11244308(PQKBTitleCode)TC0000316925(PQKBWorkID)10288009(PQKB)10786502(DE-He213)978-3-540-46258-3(MiAaPQ)EBC3068667(PPN)123138906(EXLCZ)99100000000028378320100325d2006 u| 0engurnn|008mamaatxtccrComputer Vision Approaches to Medical Image Analysis Second International ECCV Workshop, CVAMIA 2006, Graz, Austria, May 12, 2006, Revised Papers /edited by Reinhard R. Beichel, Milan Sonka1st ed. 2006.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2006.1 online resource (XII, 264 p.) Image Processing, Computer Vision, Pattern Recognition, and Graphics,3004-9954 ;4241Bibliographic Level Mode of Issuance: Monograph3-540-46257-0 Includes bibliographical references and index.Clinical Applications -- Melanoma Recognition Using Representative and Discriminative Kernel Classifiers -- Detection of Connective Tissue Disorders from 3D Aortic MR Images Using Independent Component Analysis -- Comparing Ensembles of Learners: Detecting Prostate Cancer from High Resolution MRI -- Accurate Measurement of Cartilage Morphology Using a 3D Laser Scanner -- Image Registration -- Quantification of Growth and Motion Using Non-rigid Registration -- Image Registration Accuracy Estimation Without Ground Truth Using Bootstrap -- SIFT and Shape Context for Feature-Based Nonlinear Registration of Thoracic CT Images -- Consistent and Elastic Registration of Histological Sections Using Vector-Spline Regularization -- Image Segmentation and Analysis -- Comparative Analysis of Kernel Methods for Statistical Shape Learning -- Segmentation of Dynamic Emission Tomography Data in Projection Space -- A Framework for Unsupervised Segmentation of Multi-modal Medical Images -- Poster Session -- An Integrated Algorithm for MRI Brain Images Segmentation -- Spatial Intensity Correction of Fluorescent Confocal Laser Scanning Microscope Images -- Quasi-conformal Flat Representation of Triangulated Surfaces for Computerized Tomography -- Bony Structure Suppression in Chest Radiographs -- A Minimally-Interactive Watershed Algorithm Designed for Efficient CTA Bone Removal -- Automatic Reconstruction of Dendrite Morphology from Optical Section Stacks -- Modeling the Activity Pattern of the Constellation of Cardiac Chambers in Echocardiogram Videos -- A Study on the Influence of Image Dynamics and Noise on the JPEG 2000 Compression Performance for Medical Images -- Fast Segmentation of the Mitral Valve Leaflet in Echocardiography -- Three Dimensional Tissue Classifications in MR Brain Images -- 3-D UltrasoundProbe Calibration for Computer-Guided Diagnosis and Therapy.Medical imaging and medical image analysis are developing rapidly. While m- ical imaging has already become a standard of modern medical care, medical image analysis is still mostly performed visually and qualitatively. The ev- increasing volume of acquired data makes it impossible to utilize them in full. Equally important, the visual approaches to medical image analysis are known to su?er from a lack of reproducibility. A signi?cant researche?ort is devoted to developing algorithms for processing the wealth of data available and extracting the relevant information in a computerized and quantitative fashion. Medical imaging and image analysis are interdisciplinary areas combining electrical, computer, and biomedical engineering; computer science; mathem- ics; physics; statistics; biology; medicine; and other ?elds. Medical imaging and computer vision, interestingly enough, have developed and continue developing somewhat independently. Nevertheless, bringing them together promises to b- e?t both of these ?elds. This was the second time that a satellite workshop,solely devoted to medical image analysis issues, was held in conjunction with the European Conference on Computer Vision (ECCV), and we are optimistic that this will become a tradition at ECCV. We received 38 full-length paper submissions to the second Computer Vision Approaches to Medical Image Analysis (CVAMIA) Workshop, out of which 10 were accepted for oral and 11 for poster presentation after a rigorous peer-review process. In addition, the workshop included three invited talks. The ?rst was given by Maryellen Giger from the University of Chicago, USA — titled “Multi-Modality Breast CADx”.Image Processing, Computer Vision, Pattern Recognition, and Graphics,3004-9954 ;4241Computer visionArtificial intelligencePattern recognition systemsComputer graphicsMedical informaticsBioinformaticsComputer VisionArtificial IntelligenceAutomated Pattern RecognitionComputer GraphicsHealth InformaticsBioinformaticsComputer vision.Artificial intelligence.Pattern recognition systems.Computer graphics.Medical informatics.Bioinformatics.Computer Vision.Artificial Intelligence.Automated Pattern Recognition.Computer Graphics.Health Informatics.Bioinformatics.616.07/54Beichel Reinhard R1759805Sonka Milan28581Workshop on Computer Vision Approaches to Medical Image Analysis.MiAaPQMiAaPQMiAaPQBOOK9910484692903321Computer vision approaches to medical image analysis4198457UNINA