| 000 | 07424cam a2200829 a 4500 | ||
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| 001 | ocn676700610 | ||
| 003 | OCoLC | ||
| 005 | 20250703160243.0 | ||
| 006 | m o d | ||
| 007 | cr cn||||||||| | ||
| 008 | 101101s2010 gw a ob 101 0 eng d | ||
| 040 |
_aGW5XE _beng _epn _cGW5XE _dOUN _dCEF _dOCLCQ _dCUS _dIAD _dE7B _dOCLCQ _dOCLCA _dOCLCF _dBEDGE _dDKDLA _dOCLCQ _dOCLCO _dYDXCP _dOCL _dOCLCO _dEBLCP _dOCLCQ _dOCLCO _dOCLCQ _dSOI _dESU _dUAB _dIOG _dOCLCQ _dU3W _dAU@ _dWYU _dOCLCO _dOL$ _dOCLCQ _dOCLCA _dOCLCQ _dLQU _dSFB _dCOM _dOCLCO _dOCLCQ _dOCLCO _dOCLCQ _dOCLCL _dOCLCA |
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| 020 | _a9783642159480 | ||
| 020 | _a3642159486 | ||
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_z9783642159473 _q(pbk.) |
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_a10.1007/978-3-642-15948-0 _2doi |
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| 024 | 7 | _a10.1007/978-3-642-15 | |
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_a(OCoLC)676700610 _z(OCoLC)664133067 _z(OCoLC)698586813 _z(OCoLC)769768227 _z(OCoLC)1066632540 _z(OCoLC)1086925087 _z(OCoLC)1135579596 |
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| 037 |
_a978-3-642-15947-3 _bSpringer _nhttp://www.springerlink.com |
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_aQ325.5 _b.M56 2010 |
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_aR _2lcco |
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_a006.3/1 _222 |
| 049 | _aMAIN | ||
| 111 | 2 |
_aMLMI (Workshop) _n(1st : _d2010 : _cBeijing, China) _940567 |
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| 245 | 1 | 0 |
_aMachine learning in medical imaging : _bfirst international workshop, MLMI 2010, held in conjunction with MICCAI 2010, Beijing, China, September 20, 2010, proceedings / _cFei Wang [and others] (eds.). |
| 260 |
_aBerlin : _bSpringer, _c2010. |
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| 300 |
_a1 online resource (ix, 192 pages) : _billustrations |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aLecture notes in computer science, _x0302-9743 ; _v6357 |
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| 490 | 1 | _aLNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics | |
| 504 | _aIncludes bibliographical references and author index. | ||
| 505 | 0 | _aFast Automatic Detection of Calcified Coronary Lesions in 3D Cardiac CT Images -- Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries -- Content-Based Medical Image Retrieval with Metric Learning via Rank Correlation -- A Hyper-parameter Inference for Radon Transformed Image Reconstruction Using Bayesian Inference -- Patch-Based Generative Shape Model and MDL Model Selection for Statistical Analysis of Archipelagos -- Prediction of Dementia by Hippocampal Shape Analysis -- Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis -- Appearance Normalization of Histology Slides -- Parallel Mean Shift for Interactive Volume Segmentation -- Soft Tissue Discrimination Using Magnetic Resonance Elastography with a New Elastic Level Set Model -- Fast and Automatic Heart Isolation in 3D CT Volumes: Optimal Shape Initialization -- Relation-Aware Spreadsheets for Multimodal Volume Segmentation and Visualization -- A Bayesian Learning Application to Automated Tumour Segmentation for Tissue Microarray Analysis -- Generalized Sparse Classifiers for Decoding Cognitive States in fMRI -- Manifold Learning for Biomarker Discovery in MR Imaging -- Optimal Live Cell Tracking for Cell Cycle Study Using Time-Lapse Fluorescent Microscopy Images -- Fully Automatic Joint Segmentation for Computer-Aided Diagnosis and Planning -- Accurate Identification of MCI Patients via Enriched White-Matter Connectivity Network -- Feature Extraction for fMRI-Based Human Brain Activity Recognition -- Sparse Spatio-temporal Inference of Electromagnetic Brain Sources -- Optimal Gaussian Mixture Models of Tissue Intensities in Brain MRI of Patients with Multiple-Sclerosis -- Preliminary Study on Appearance-Based Detection of Anatomical Point Landmarks in Body Trunk CT Images -- Principal-Component Massive-Training Machine-Learning Regression for False-Positive Reduction in Computer-Aided Detection of Polyps in CT Colonography. | |
| 520 | _aThe first International Workshop on Machine Learning in Medical Imaging, MLMI 2010, was held at the China National Convention Center, Beijing, China on Sept- ber 20, 2010 in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2010. Machine learning plays an essential role in the medical imaging field, including image segmentation, image registration, computer-aided diagnosis, image fusion, ima- guided therapy, image annotation, and image database retrieval. With advances in me- cal imaging, new imaging modalities, and methodologies such as cone-beam/multi-slice CT, 3D Ultrasound, tomosynthesis, diffusion-weighted MRI, electrical impedance to- graphy, and diffuse optical tomography, new machine-learning algorithms/applications are demanded in the medical imaging field. Single-sample evidence provided by the patient's imaging data is often not sufficient to provide satisfactory performance; the- fore tasks in medical imaging require learning from examples to simulate a physician's prior knowledge of the data. The MLMI 2010 is the first workshop on this topic. The workshop focuses on major trends and challenges in this area, and works to identify new techniques and their use in medical imaging. Our goal is to help advance the scientific research within the broad field of medical imaging and machine learning. The range and level of submission for this year's meeting was of very high quality. Authors were asked to submit full-length papers for review. A total of 38 papers were submitted to the workshop in response to the call for papers. | ||
| 650 | 0 |
_aMachine learning _vCongresses. _915308 |
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| 650 | 0 |
_aDiagnostic imaging _xData processing _vCongresses. _923895 |
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| 650 | 6 |
_aApprentissage automatique _vCongrès. _920183 |
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| 650 | 6 |
_aImagerie pour le diagnostic _xInformatique _vCongrès. _927835 |
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| 650 | 7 |
_aInformatique. _2eclas _914930 |
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| 650 | 7 |
_aDiagnostic imaging _xData processing _2fast _923897 |
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| 650 | 7 |
_aMachine learning _2fast _91680 |
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| 650 | 7 |
_aBildgebendes Verfahren _2gnd |
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| 650 | 7 |
_aMaschinelles Lernen _2gnd |
|
| 651 | 7 |
_aPeking <2010> _2swd _939011 |
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| 655 | 2 |
_aCongress _911670 |
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| 655 | 7 |
_aproceedings (reports) _2aat |
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| 655 | 7 |
_aConference papers and proceedings _2fast _96065 |
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| 655 | 7 |
_aConference papers and proceedings. _2lcgft _96065 |
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| 655 | 7 |
_aActes de congrès. _2rvmgf _9609890 |
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| 700 | 1 |
_aWang, Fei. _940570 |
|
| 758 |
_ihas work: _aMachine learning in medical imaging (Text) _1https://id.oclc.org/worldcat/entity/E39PCFGBFx9Q3fGytwCJ7m8t8C _4https://id.oclc.org/worldcat/ontology/hasWork |
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| 776 | 0 | 8 |
_iPrint version: _tMachine learning in medical imaging. _dBerlin : Springer, 2010 _z9783642159473 _w(OCoLC)663945274 |
| 830 | 0 |
_aLecture notes in computer science ; _v6357. |
|
| 830 | 0 |
_aLNCS sublibrary. _nSL 6, _pImage processing, computer vision, pattern recognition, and graphics. _921253 |
|
| 856 | 4 | 0 | _uhttps://link.springer.com/10.1007/978-3-642-15948-0 |
| 938 |
_aProQuest Ebook Central _bEBLB _nEBL3065848 |
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| 938 |
_aebrary _bEBRY _nebr10417373 |
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_aYBP Library Services _bYANK _n3481453 |
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