LEADER 06823nam 22007815 450 001 996465976003316 005 20200706161339.0 010 $a3-540-46258-9 024 7 $a10.1007/11889762 035 $a(CKB)1000000000283783 035 $a(SSID)ssj0000316925 035 $a(PQKBManifestationID)11244308 035 $a(PQKBTitleCode)TC0000316925 035 $a(PQKBWorkID)10288009 035 $a(PQKB)10786502 035 $a(DE-He213)978-3-540-46258-3 035 $a(MiAaPQ)EBC3068667 035 $a(PPN)123138906 035 $a(EXLCZ)991000000000283783 100 $a20100325d2006 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aComputer Vision Approaches to Medical Image Analysis$b[electronic resource] $eSecond International ECCV Workshop, CVAMIA 2006, Graz, Austria, May 12, 2006, Revised Papers /$fedited by Reinhard R. Beichel, Milan Sonka 205 $a1st ed. 2006. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2006. 215 $a1 online resource (XII, 264 p.) 225 1 $aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;$v4241 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-46257-0 320 $aIncludes bibliographical references and index. 327 $aClinical 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 Ultrasound Probe Calibration for Computer-Guided Diagnosis and Therapy. 330 $aMedical imaging and medical image analysis are developing rapidly. While m- ical imaging has already become a standard of modern medical care, medical image analysis is still mostly performed visually and qualitatively. The ev- increasing volume of acquired data makes it impossible to utilize them in full. Equally important, the visual approaches to medical image analysis are known to su?er from a lack of reproducibility. A signi?cant researche?ort is devoted to developing algorithms for processing the wealth of data available and extracting the relevant information in a computerized and quantitative fashion. Medical imaging and image analysis are interdisciplinary areas combining electrical, computer, and biomedical engineering; computer science; mathem- ics; physics; statistics; biology; medicine; and other ?elds. Medical imaging and computer vision, interestingly enough, have developed and continue developing somewhat independently. Nevertheless, bringing them together promises to b- e?t both of these ?elds. This was the second time that a satellite workshop,solely devoted to medical image analysis issues, was held in conjunction with the European Conference on Computer Vision (ECCV), and we are optimistic that this will become a tradition at ECCV. We received 38 full-length paper submissions to the second Computer Vision Approaches to Medical Image Analysis (CVAMIA) Workshop, out of which 10 were accepted for oral and 11 for poster presentation after a rigorous peer-review process. In addition, the workshop included three invited talks. The ?rst was given by Maryellen Giger from the University of Chicago, USA ? titled ?Multi-Modality Breast CADx?. 410 0$aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;$v4241 606 $aOptical data processing 606 $aArtificial intelligence 606 $aPattern recognition 606 $aComputer graphics 606 $aHealth informatics 606 $aBioinformatics 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aComputer Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22013 606 $aHealth Informatics$3https://scigraph.springernature.com/ontologies/product-market-codes/H28009 606 $aBioinformatics$3https://scigraph.springernature.com/ontologies/product-market-codes/L15001 615 0$aOptical data processing. 615 0$aArtificial intelligence. 615 0$aPattern recognition. 615 0$aComputer graphics. 615 0$aHealth informatics. 615 0$aBioinformatics. 615 14$aImage Processing and Computer Vision. 615 24$aArtificial Intelligence. 615 24$aPattern Recognition. 615 24$aComputer Graphics. 615 24$aHealth Informatics. 615 24$aBioinformatics. 676 $a616.07/54 702 $aBeichel$b Reinhard R$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSonka$b Milan$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aWorkshop on Computer Vision Approaches to Medical Image Analysis 906 $aBOOK 912 $a996465976003316 996 $aComputer Vision Approaches to Medical Image Analysis$9772580 997 $aUNISA